Search results for: food frequency and biomedical data

Authors: Cornelius Femi Popoola

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Nigerian manufacturing industry, particularly the flour producing firms play vital roles in Nigerian economy. This sector’s quality management practice is given a little attention along with organizational factors that hinder successful practice of total quality management which needs to be documented. Honeywell Flour Mills Plc operate in Nigeria with an appreciable number of products that serves this sector of the economy. Internal-external disposition of the company and total quality practice of the company deserve some elucidations. Hence, this study examined the influence of organizational factors on total quality management practice of Nigerian manufacturing industry, using Honeywell Flour Mills Plc as a case study. The study employed the correlational type of descriptive survey research design. The population consisted of 656 staff of Honeywell Flour Mills Plc, out of which 235 members were selected through scientific sampling method developed by Paler-Calmorin and Calmorin. A total of 235 copies of questionnaires titled 'Organisational Factors and Total Quality Management Practices (QF-TQM) Questionnaire' were administered with a response rate of 66 copies returned. The following variables were applied internal organisational factors (IOFs), external organizational factors (EOFs) and total quality management (TQM). Data generated were analysed using frequency distribution and regression analysis at 0.05 level. The findings revealed that IOFs positively and significantly related with TQM (r = .147**, N= 64, P(.000) < .01). Also, EOFs negatively and significantly related with TQM (r = -.117, N= 64, P(.000) < .01). Findings showed that internal and external organizational factors jointly influenced TQM practiced in F₍₂,₆₁₎=22.250; R²=.629; Adj.R²=.603; P(.000) < .05). The study concluded that organizational factors are determinants of TQM practice in Nigerian manufacturing industry. It is recommended that both internal and external organizational factors influencing TQM practices should be considered in the development of TQM strategies.

Keywords: external organizational factors, internal organisational factors, Nigerian manufacturing industry, total quality management

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Authors: Amirreza Fazely Hamedani, Muzzamil Aziz, Philipp Wieder, Ramin Yahyapour

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Software-defined networking in recent years came into the sight of so many network designers as a successor to the traditional networking. Unlike traditional networks where control and data planes engage together within a single device in the network infrastructure such as switches and routers, the two planes are kept separated in software-defined networks (SDNs). All critical decisions about packet routing are made on the network controller, and the data level devices forward the packets based on these decisions. This type of network is vulnerable to DDoS attacks, degrading the overall functioning and performance of the network by continuously injecting the fake flows into it. This increases substantial burden on the controller side, and the result ultimately leads to the inaccessibility of the controller and the lack of network service to the legitimate users. Thus, the protection of this novel network architecture against denial of service attacks is essential. In the world of cybersecurity, attacks and new threats emerge every day. It is essential to have tools capable of managing and analyzing all this new information to detect possible attacks in real-time. These tools should provide a comprehensive solution to automatically detect, predict and prevent abnormalities in the network. Big data encompasses a wide range of studies, but it mainly refers to the massive amounts of structured and unstructured data that organizations deal with on a regular basis. On the other hand, it regards not only the volume of the data; but also that how data-driven information can be used to enhance decision-making processes, security, and the overall efficiency of a business. This paper presents an intelligent big data framework as a solution to handle illegitimate traffic burden on the SDN network created by the numerous DDoS attacks. The framework entails an efficient defence and monitoring mechanism against DDoS attacks by employing the state of the art machine learning techniques.

Keywords: apache spark, apache kafka, big data, DDoS attack, machine learning, SDN network

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Authors: Negar Riazifar, Nigel G. Stocks

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This paper proposes strategies in level crossing (LC) sampling and reconstruction that provide alias-free high-fidelity signal reconstruction for speech signals without exponentially increasing sample number with increasing bit-depth. We introduce methods in LC sampling that reduce the sampling rate close to the Nyquist frequency even for large bit-depth. The results indicate that larger variation in the sampling intervals leads to an alias-free sampling scheme; this is achieved by either reducing the bit-depth or adding jitter to the system for high bit-depths. In conjunction with windowing, the signal is reconstructed from the LC samples using an efficient Toeplitz reconstruction algorithm.

Keywords: alias-free, level crossing sampling, spectrum, trigonometric polynomial

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Authors: Y. Melis, E. Apicella, E. Dozio, L. Mendolicchio

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Introduction: Feeding and Eating Disorders (FED) represent the psychiatric pathology with the highest mortality rate and one of the major disorders with the highest psychiatric and clinical comorbidity. The vagus nerve represents one of the main components of the sympathetic and parasympathetic nervous system and is involved in important neurophysiological functions. In FED, there is a spectrum of symptoms which with TaVNS (Transcutaneous Auricular Vagus Nerve Stimulation) therapy, is possible to have a therapeutic efficacy. Materials and Methods: Sample subjects are composed of 15 female subjects aged > 18 ± 51. Admitted to a psychiatry community having been diagnosed according to DSM-5: anorexia nervosa (AN) (N= 9), bulimia nervosa (BN) (N= 5), binge eating disorder (BED) (N= 1). The protocol included 9 weeks of Ta-VNS stimulation at a frequency of 1.5-3.5 mA for 4 hours per day. The variables detected are the following: Heart Rate Variability (HRV), Hamilton Depression Rating Scale (HAMD-HDRS-17), Body Mass Index (BMI), Beck Anxiety Index (BAI). Results: Data analysis showed statistically significant differences between recording times (p > 0.05) in HAM-D (t0 = 18.28 ± 5.31; t4 = 9.14 ± 7.15), in BAI (t0 = 24.7 ± 10.99; t4 = 13.8 ± 7.0). The reported values show how during (T0-T4) the treatment there is a decay of the degree in the depressive state, in the state of anxiety, and an improvement in the value of BMI. In particular, the BMI in the AN-BN sub-sample had a minimum gain of 5% and a maximum of 11%. The analysis of HRV did not show a clear change among subjects, thus confirming the discordance of the activity of the sympathetic and parasympathetic nervous system in FED. Conclusions: Although the sample does not possess a relevant value to determine long-term efficacy of Ta-VNS or on a larger population, this study reports how the application of neuro-stimulation in FED may become a further approach therapeutic. Indeed, substantial improvements are highlighted in the results and confirmed hypotheses proposed by the study.

Keywords: feeding and eating disorders, neurostimulation, anxiety disorders, depression

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Authors: Kayode Balogun, Femi Ayoola

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Crime is at alarming rate in this part of world and there are many factors that are contributing to this antisocietal behaviour both among the youths and old. In this work, principal component analysis (PCA) was used as a tool to reduce the dimensionality and to really know those variables that were crime prone in the study region. Data were collected on twenty-eight crime variables from National Bureau of Statistics (NBS) databank for a period of fifteen years, while retaining as much of the information as possible. We use PCA in this study to know the number of major variables and contributors to the crime in the Southwest Nigeria. The results of our analysis revealed that there were eight principal variables have been retained using the Scree plot and Loading plot which implies an eight-equation solution will be appropriate for the data. The eight components explained 93.81% of the total variation in the data set. We also found that the highest and commonly committed crimes in the Southwestern Nigeria were: Assault, Grievous Harm and Wounding, theft/stealing, burglary, house breaking, false pretence, unlawful arms possession and breach of public peace.

Keywords: crime rates, data, Southwest Nigeria, principal component analysis, variables

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Authors: Hyun-Woo Cho

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Detection of incipient abnormal events in production processes is important to improve safety and reliability of manufacturing operations and reduce losses caused by failures. The construction of calibration models for predicting faulty conditions is quite essential in making decisions on when to perform preventive maintenance. This paper presents a multivariate calibration monitoring approach based on the statistical analysis of process measurement data. The calibration model is used to predict faulty conditions from historical reference data. This approach utilizes variable selection techniques, and the predictive performance of several prediction methods are evaluated using real data. The results shows that the calibration model based on supervised probabilistic model yielded best performance in this work. By adopting a proper variable selection scheme in calibration models, the prediction performance can be improved by excluding non-informative variables from their model building steps.

Keywords: calibration model, monitoring, quality improvement, feature selection

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Authors: Parashram Jakappa Patil

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India is the global leader in world cashew business and cashew-nut industry is one of the important food processing industries in world. However India is the largest producer, processor, exporter and importer eschew in the world. India is providing cashew to the rest of the world. India is meeting world demand of cashew. India has a tremendous potential of cashew production and export to other countries. Every year India earns more than 2000 cores rupees through cashew trade. Cashew industry is one of the important small scale industries in the country which is playing significant role in rural development. It is generating more than 400000 jobs at remote area and 95% cashew worker are women, it is giving income to poor cashew farmers, majority cashew processing units are small and cottage, it is helping to stop migration from young farmers for employment opportunities, it is motivation rural entrepreneurship development and it is also helping to environment protection etc. Hence India cashew business is very important agribusiness in India which has potential make inclusive development. World Bank and IMF recognized cashew-nut industry is one the important tool for poverty eradication at global level. It shows important of cashew business and its strong existence in India. In spite of such huge potential cashew processing industry is facing different problems such as lack of infrastructure ability, lack of supply of raw cashew, lack of availability of finance, collection of raw cashew, unavailability of warehouse, marketing of cashew kernels, lack of technical knowledge and especially processing technology and packaging of finished products. This industry has great prospects such as scope for more cashew cultivation and cashew production, employment generation, formation of cashew processing units, alcohols production from cashew apple, shield oil production, rural development, poverty elimination, development of social and economic backward class and environment protection etc. This industry has domestic as well as foreign market; India has tremendous potential in this regard. The cashew is a poor men’s crop but rich men’s food. The cashew is a source of income and livelihood for poor farmers. Cashew-nut industry may play very important role in the development of hilly region. The objectives of this paper are to identify problems of cashew processing and use of processing technology, problems of cashew kernel packaging, evolving of cashew processing technology over the year and its impact on final product and impact of good processing by adopting appropriate technology packaging on international trade of cashew-nut. The most important problem of cashew processing industry is that is processing and packaging. Bad processing reduce the quality of cashew kernel at large extent especially broken of cashew kernel which has very less price in market compare to whole cashew kernel and not eligible for export. On the other hand if there is no good packaging of cashew kernel will get moisture which destroy test of it. International trade of cashew-nut is depend of two things one is cashew processing and other is packaging. This study has strong relevance because cashew-nut industry is the labour oriented, where processing technology is not playing important role because 95% processing work is manual. Hence processing work was depending on physical performance of worker which makes presence of large workforce inevitable. There are many cashew processing units closed because they are not getting sufficient work force. However due to advancement in technology slowly this picture is changing and processing work get improve. Therefore it is interesting to explore all the aspects in context of cashew processing and packaging of cashew business.

Keywords: cashew, processing technology, packaging, international trade, change

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Authors: Muhammad Atif Randhawa, Adnan Amjad, Muhammad Nadeem

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Potato (Solanum tuberosum) popularly known as ‘the king of vegetables’, has emerged as fourth most important food crop after rice, wheat and maize. Potato contains carbohydrates, minerals, vitamins and antioxidants. The antioxidants of potatoes especially vitamin C helps in reducing cancer, cardiovascular diseases and high blood pressure by binding free radicals. Physical characteristics and some major chemical properties of potato tubers at fresh and stored stages were investigated. Two varieties of potatoes, Sante (V1) having white colour and Lal moti (V2) with red colour were stored for 3 months and analysis were performed after each month interval. Physical and chemical attributes including weight loss, sprouting, specific gravity, pH, total sugars (reducing and non-reducing sugars) and vitamin C were analyzed before and after storage. Value of weight loss at zero day was null but it increased to 6.45% after 90 days on average in both cultivars and sprouting increased gradually at the end of 90 days. Moreover total sugars were 3.10% at zero day but increased to 9.30% after 90 days. Ascorbic acid was decreased during storage from 17.49(mg/100g) to 3.79. Both varieties of potato were stored at 60C and 120C temperatures with 85% relative humidity in order to prolong their acceptability in the market. The storage conditions influence the potatoes quality and consequently their acceptability to consumer. The data was analyzed statistically and clarifies that total sugars, weight loss, sprouting and specific gravity increase during the storage period while ascorbic acid (Vit-C) and pH decreased. Among both varieties that were stored at 60C and 120C, Sante (V1) was better than Lal moti (V2) due to less physicochemical and quality changes at 60C as compared to store at 120C.

Keywords: physicochemical, potato, quality attributes, storage

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Authors: Rupali Bhardwaj

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Cryptography is the science of using mathematics to encrypt and decrypt data; the data are converted into some other gibberish form, and then the encrypted data are transmitted. The primary purpose of this paper is to provide two levels of security through a two-step process, rather than transmitted the message bits directly, first encrypted it using 2D cellular automata and then scrambled with Arnold Cat Map transformation; it provides an additional layer of protection and reduces the chance of the transmitted message being detected. A comparative analysis on effectiveness of scrambling technique is provided by scrambling degree measurement parameters i.e. Gray Difference Degree (GDD) and Correlation Coefficient.

Keywords: scrambling, cellular automata, Arnold cat map, game of life, gray difference degree, correlation coefficient

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Authors: Naveed Ghani, Samreen Javed

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In today’s heterogeneous network environment, there is a growing demand for distrust clients to jointly execute secure network to prevent from malicious attacks as the defining task of propagating malicious code is to locate new targets to attack. Residual risk is always there no matter what solutions are implemented or whet so ever security methodology or standards being adapted. Security is the first and crucial phase in the field of Computer Science. The main aim of the Computer Security is gathering of information with secure network. No one need wonder what all that malware is trying to do: It's trying to steal money through data theft, bank transfers, stolen passwords, or swiped identities. From there, with the help of our survey we learn about the importance of white listing, antimalware programs, security patches, log files, honey pots, and more used in banks for financial data protection but there’s also a need of implementing the IPV6 tunneling with Crypto data transformation according to the requirements of new technology to prevent the organization from new Malware attacks and crafting of its own messages and sending them to the target. In this paper the writer has given the idea of implementing IPV6 Tunneling Secessions on private data transmission from financial organizations whose secrecy needed to be safeguarded.

Keywords: network worms, malware infection propagating malicious code, virus, security, VPN

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Authors: Abdallah Al-ZoubI, Mamoun Dmour

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The spectrum of IoT devices is becoming widely diversified, entering almost all possible fields and finding applications in industry, health, finance, logistics, education, to name a few. The IoT active endpoint sensors and devices exceeded the 12 billion mark in 2021 and are expected to reach 27 billion in 2025, with over $34 billion in total market value. This sheer rise in numbers and use of IoT devices bring with it considerable concerns regarding data storage, analysis, manipulation and protection. IoT Blockchain-based systems have recently been proposed as a decentralized solution for large-scale data storage and protection. COVID-19 has actually accelerated the desire to utilize IoT devices as it impacted both demand and supply and significantly affected several regions due to logistic reasons such as supply chain interruptions, shortage of shipping containers and port congestion. An IoT-blockchain system is proposed to handle big data generated by a distributed network of sensors and controllers in an interactive manner. The system is designed using the Ethereum platform, which utilizes smart contracts, programmed in solidity to execute and manage data generated by IoT sensors and devices. such as Raspberry Pi 4, Rasbpian, and add-on hardware security modules. The proposed system will run a number of applications hosted by a local machine used to validate transactions. It then sends data to the rest of the network through InterPlanetary File System (IPFS) and Ethereum Swarm, forming a closed IoT ecosystem run by blockchain where a number of distributed IoT devices can communicate and interact, thus forming a closed, controlled environment. A prototype has been deployed with three IoT handling units distributed over a wide geographical space in order to examine its feasibility, performance and costs. Initial results indicated that big IoT data retrieval and storage is feasible and interactivity is possible, provided that certain conditions of cost, speed and thorough put are met.

Keywords: IoT devices, blockchain, Ethereum, big data

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Authors: Abdul-Rahman Al-Ali

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As the number of mobile devices is growing exponentially, it is estimated to connect about 50 million devices to the Internet by the year 2020. At the end of this decade, it is expected that an average of eight connected devices per person worldwide. The 50 billion devices are not mobile phones and data browsing gadgets only, but machine-to-machine and man-to-machine devices. With such growing numbers of devices the Internet of Things (I.o.T) concept is one of the emerging technologies as of recently. Within the smart grid technologies, smart home appliances, Intelligent Electronic Devices (IED) and Distributed Energy Resources (DER) are major I.o.T objects that can be addressable using the IPV6. These objects are called the smart grid internet of things (SG-I.o.T). The SG-I.o.T generates big data that requires high-speed computing infrastructure, widespread computer networks, big data storage, software, and platforms services. A company’s utility control and data centers cannot handle such a large number of devices, high-speed processing, and massive data storage. Building large data center’s infrastructure takes a long time, it also requires widespread communication networks and huge capital investment. To maintain and upgrade control and data centers’ infrastructure and communication networks as well as updating and renewing software licenses which collectively, requires additional cost. This can be overcome by utilizing the emerging computing paradigms such as cloud computing. This can be used as a smart grid enabler to replace the legacy of utilities data centers. The talk will highlight the role of I.o.T, cloud computing services and their development models within the smart grid technologies.

Keywords: intelligent electronic devices (IED), distributed energy resources (DER), internet, smart home appliances

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Authors: Shishen Xie, Yingda L. Xie

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Tuberculosis (TB) is a potentially serious infectious disease that remains a health concern. The Interferon Gamma Release Assay (IGRA) is a blood test to find out if an individual is tuberculous positive or negative. This study applies statistical analysis to the clinical data of interferon-gamma levels of seventy-three subjects who diagnosed pulmonary TB in an anti-tuberculous treatment. Data analysis is performed to determine if there is a significant decline in interferon-gamma levels for the subjects during a period of six months, and to infer if the anti-tuberculous treatment is effective.

Keywords: data analysis, interferon gamma release assay, statistical methods, tuberculosis infection

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Authors: Zainab Mutlaq Ibrahim, Mohamed Bader-El-Den, Mihaela Cocea

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Students' textual feedback can hold unique patterns and useful information about learning process, it can hold information about advantages and disadvantages of teaching methods, assessment components, facilities, and other aspects of teaching. The results of analysing such a feedback can form a key point for institutions’ decision makers to advance and update their systems accordingly. This paper proposes a data mining framework for analysing end of unit general textual feedback using part of speech feature (PoS) with four machine learning algorithms: support vector machines, decision tree, random forest, and naive bays. The proposed framework has two tasks: first, to use the above algorithms to build an optimal model that automatically classifies the whole data set into two subsets, one subset is tailored to assessment practices (assessment related), and the other one is the non-assessment related data. Second task to use the same algorithms to build an optimal model for whole data set, and the new data subsets to automatically detect their sentiment. The significance of this paper is to compare the performance of the above four algorithms using part of speech feature to the performance of the same algorithms using n-grams feature. The paper follows Knowledge Discovery and Data Mining (KDDM) framework to construct the classification and sentiment analysis models, which is understanding the assessment domain, cleaning and pre-processing the data set, selecting and running the data mining algorithm, interpreting mined patterns, and consolidating the discovered knowledge. The results of this paper experiments show that both models which used both features performed very well regarding first task. But regarding the second task, models that used part of speech feature has underperformed in comparison with models that used unigrams and bigrams.

Keywords: assessment, part of speech, sentiment analysis, student feedback

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Authors: Olufunmilola A. Abiodun, Adegbola O. Dauda, Ayobami Ojo, Samson A. Oyeyinka

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Blighia sapida (Ackee) seed is a neglected and under-utilised crop. The fruit is cultivated for the aril which is used as meat substitute in soup while the seed is discarded. The seed is toxic due to the presence of hypoglycin which causes vomiting and death. The seed is shining black and bigger than the legume seeds. The seed contains high starch content which could serve as a cheap source of starch hereby reducing wastage of the crop during its season. Native starch had limitation in their use; therefore, modification of starch had been reported to improve the functional properties of starches. Therefore, this work determined the effect of modification on the properties of Blighia sapida seed starch. Blighia sapida seed was dehulled manually, milled and the starch extracted using standard method. The starch was subjected to modification using four methods (acid, alkaline, oxidized and acetylated methods). The morphological structure, form factor, granule size, amylose, swelling power, hypoglycin and pasting properties of the starches were determined. The structure of Blighia sapida using light microscope showed that the seed starch demonstrated an oval, round, elliptical, dome-shaped and also irregular shape. The form factors of the starch ranged from 0.32-0.64. Blighia sapida seed starches were smaller in granule sizes ranging from 2-6 µm. Acid modified starch had the highest amylose content (24.83%) and was significantly different ( < 0.05) from other starches. Blighia sapida seed starches showed a progressive increase in swelling power as temperature increased in native, acidified, alkalized, oxidized and acetylated starches but reduced with increasing temperature in pregelatinized starch. Hypoglycin A ranged from 3.89 to 5.74 mg/100 g with pregelatinized starch having the lowest value and alkalized starch having the highest value. Hypoglycin B ranged from 7.17 to 8.47 mg/100 g. Alkali-treated starch had higher peak viscosity (3973 cP) which was not significantly different (p > 0.05) from the native starch. Alkali-treated starch also was significantly different (p > 0.05) from other starches in holding strength value while acetylated starch had higher breakdown viscosity (1161.50 cP). Native starch was significantly different (p > 0.05) from other starches in final and setback viscosities. Properties of Blighia sapida modified starches showed that it could be used as a source of starch in food and other non-food industries and the toxic compound found in the starch was very low when compared to lethal dosage.

Keywords: Blighia sapida seed, modification, starch, hypoglycin

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Authors: Sanaz Kavianpour, Zuraini Ismail, Bharanidharan Shanmugam

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Social Network Sites (SNSs) can be served as an invaluable platform to transfer the information across a large number of individuals. A substantial component of communicating and managing information is to identify which individual will influence others in propagating information and also whether dissemination of information in the absence of social signals about that information will be occurred or not. Classifying the final audience of social data is difficult as controlling the social contexts which transfers among individuals are not completely possible. Hence, undesirable information diffusion to an unauthorized individual on SNSs can threaten individuals’ privacy. This paper highlights the information diffusion in SNSs and moreover it emphasizes the most significant privacy issues to individuals of SNSs. The goal of this paper is to propose a privacy-preserving model that has urgent regards with individuals’ data in order to control availability of data and improve privacy by providing access to the data for an appropriate third parties without compromising the advantages of information sharing through SNSs.

Keywords: anonymization algorithm, classification algorithm, information diffusion, privacy, social network sites

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Authors: Alhaji M. H. Conteh, Xiangbin Yan, Issa Fofana, Brima Gegbe, Tamba I. Isaac

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Rice grain is Sierra Leone’s staple food and the nation imports over 120,000 metric tons annually due to a shortfall in its cultivation. Thus, the insufficient level of the crop's cultivation in Sierra Leone is caused by many problems and this led to the endlessly widening supply and demand for the crop within the country. Consequently, this has instigated the government to spend huge money on the importation of this grain that would have been otherwise cultivated domestically at a cheaper cost. Hence, this research attempts to explore the response of rice supply with respect to its demand in Sierra Leone within the period 1980-2010. The Nerlovian adjustment model to the Sierra Leone rice data set within the period 1980-2010 was used. The estimated trend equations revealed that time had significant effect on output, productivity (yield) and area (acreage) of rice grain within the period 1980-2010 and this occurred generally at the 1% level of significance. The results showed that, almost the entire growth in output had the tendency to increase in the area cultivated to the crop. The time trend variable that was included for government policy intervention showed an insignificant effect on all the variables considered in this research. Therefore, both the short-run and long-run price response was inelastic since all their values were less than one. From the findings above, immediate actions that will lead to productivity growth in rice cultivation are required. To achieve the above, the responsible agencies should provide extension service schemes to farmers as well as motivating them on the adoption of modern rice varieties and technology in their rice cultivation ventures.

Keywords: Nerlovian adjustment model, price elasticities, Sierra Leone, trend equations

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Authors: Reza Vakili, Xiaolei Fan, Alex Walton

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The first near ambient pressure (NAP)-XPS study of CO oxidation over Pt nanoparticles (NPs) incorporated into Zr-based UiO (UiO for Universitetet i Oslo) MOFs was carried out. For this purpose, the MOF-based Catalysts were prepared by wetness impregnation (WI-PtNPs@UiO-67) and linker design (LD-PtNPs@UiO-67) methods along with PtNPs@ZrO₂ as the control catalyst. Firstly, the as-synthesized catalysts were reduced in situ prior to the operando XPS analysis. The existence of Pt(II) species was proved in UiO-67 by observing Pt 4f core level peaks at a high binding energy of 72.6 ± 0.1 eV. However, by heating the WI-PtNPs@UiO-67 catalyst in situ to 200 °C under vacuum, the higher BE components disappear, leaving only the metallic Pt 4f doublet, confirming the formation of Pt NPs. The complete reduction of LD-PtNPs@UiO-67 is achieved at 250 °C and 1 mbar H₂. To understand the chemical state of Pt NPs in UiO-67 during catalytic turnover, we analyzed the Pt 4f region using operando NAP-XPS in the temperature-programmed measurements (100-260 °C) with reference to PtNPs@ZrO₂ catalyst. CO conversion during NAP-XPS experiments with the stoichiometric mixture shows that LD-PtNPs@UiO-67 has a better CO turnover frequency (TOF, 0.066 s⁻¹ at 260 °C) than the other two (ca. 0.055 s⁻¹). Pt 4f peaks only show one chemical species present at all temperatures, but the core level BE shifts change as a function of reaction temperature, i.e., Pt 4f peak from 71.8 eV at T < 200 °C to 71.2 eV at T > 200 °C. As this higher BE state of 71.8 eV was not observed after in situ reductions of the catalysts and only once the CO/O₂ mixture was introduced, we attribute it to the surface saturation of Pt NPs with adsorbed CO. In general, the quantitative analysis of Pt 4f data from the operando NAP-XPS experiments shows that the surface chemistry of the Pt active phase in the two PtNPs@UiO-67 catalysts is the same, comparable to that of PtNPs@ZrO₂. The observed difference in the catalytic activity can be attributed to the particle sizes of Pt NPs, as well as the dispersion of active phase in the support, which are different in the three catalysts.

Keywords: CO oxidation, heterogeneous catalysis, MOFs, Metal Organic Frameworks, NAP-XPS, Near Ambient Pressure X-ray Photoelectron Spectroscopy

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Authors: A. M. Isakhanyan, F. N. Tkhruni, N. N. Yakimovich, Z. I. Kuvaeva, T. V. Khachatryan

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Introduction: At present, the simbiotics based on different genera and species of lactic acid bacteria (LAB) and yeasts are used. One of the basic properties of probiotics is presence of antimicrobial activity and therefore selection of LAB and yeast strains for their co-cultivation with the aim of increasing of the activity is topical. Since probiotic yeast and bacteria have different mechanisms of action, natural synergies between species, higher viability and increasing of antimicrobial activity might be expected from mixing both types of probiotics. Endemic strains of LAB Enterococcus faecium БТK-64, Lactobaccilus plantarum БТK-66, Pediococcus pentosus БТK-28, Lactobacillus rhamnosus БТK-109 and Kluyveromyces lactis БТX-412, Saccharomycopsis sp. БТX- 151 strains of yeast, with probiotic properties and hight antimicrobial activity, were selected. Strains are deposited in "Microbial Depository Center" (MDC) SPC "Armbiotechnology". Methods: LAB and yeast strains were isolated from different dairy products from rural households of Armenia. The genotyping by 16S rRNA sequencing for LAB and 26S RNA sequencing for yeast were used. Combined cultivation of LAB and yeast strains was carried out in the nutrient media on the basis of milk whey, in anaerobic conditions (without shaker, in a thermostat at 37oC, 48 hours). The complex preparations were obtained by purification of cell free culture broth (CFC) broth by the combination of ion-exchange chromatography and gel filtration methods. The spot-on-lawn method was applied for determination of antimicrobial activity and expressed in arbitrary units (AU/ml). Results. The obtained data showed that at the combined growth of bacteria and yeasts, the cultivation conditions (medium composition, time of growth, genera of LAB and yeasts) affected the display of antimicrobial activity. Purification of CFC broth allowed obtaining partially purified antimicrobial complex preparation which contains metabiotics from both bacteria and yeast. The complex preparation inhibited the growth of pathogenic and conditionally pathogenic bacteria, isolated from various internal organs from diseased animals and poultry with greater efficiency than the preparations derived individually alone from yeast and LAB strains. Discussion. Thus, our data shown perspectives of creation of a new class of antimicrobial preparations on the basis of combined cultivation of endemic strains of LAB and yeast. Obtained results suggest the prospect of use of the partially purified complex preparations instead antibiotics in the agriculture and for food safety. Acknowledgments: This work was supported by the RA MES State Committee of Science and Belarus National Foundation for Basic Research in the frames of the joint Armenian - Belarusian joint research project 13РБ-064.

Keywords: co-cultivation, antimicrobial activity, biosafety, metabiotics, lactic acid bacteria, yeast

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Authors: Idrissa Kayijuka

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The logistic regression and Cox regression models (proportional hazard model) at present are being employed in the analysis of prospective epidemiologic research looking into risk factors in their application on chronic diseases. However, a theoretical relationship between the two models has been studied. By definition, Cox regression model also called Cox proportional hazard model is a procedure that is used in modeling data regarding time leading up to an event where censored cases exist. Whereas the Logistic regression model is mostly applicable in cases where the independent variables consist of numerical as well as nominal values while the resultant variable is binary (dichotomous). Arguments and findings of many researchers focused on the overview of Cox and Logistic regression models and their different applications in different areas. In this work, the analysis is done on secondary data whose source is SPSS exercise data on BREAST CANCER with a sample size of 1121 women where the main objective is to show the application difference between Cox regression model and logistic regression model based on factors that cause women to die due to breast cancer. Thus we did some analysis manually i.e. on lymph nodes status, and SPSS software helped to analyze the mentioned data. This study found out that there is an application difference between Cox and Logistic regression models which is Cox regression model is used if one wishes to analyze data which also include the follow-up time whereas Logistic regression model analyzes data without follow-up-time. Also, they have measurements of association which is different: hazard ratio and odds ratio for Cox and logistic regression models respectively. A similarity between the two models is that they are both applicable in the prediction of the upshot of a categorical variable i.e. a variable that can accommodate only a restricted number of categories. In conclusion, Cox regression model differs from logistic regression by assessing a rate instead of proportion. The two models can be applied in many other researches since they are suitable methods for analyzing data but the more recommended is the Cox, regression model.

Keywords: logistic regression model, Cox regression model, survival analysis, hazard ratio

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Authors: Dominique Arrouays, Songchao Chen, Anne C. Richer-De-Forges

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Soils are at the crossing of many issues such as food and water security, sustainable energy, climate change mitigation and adaptation, biodiversity protection, human health and well-being. They deliver many ecosystem services that are essential to life on Earth. Therefore, there is a growing demand for soil information on a national and global scale. Unfortunately, many countries do not have detailed soil maps, and, when existing, these maps are generally based on more or less complex and often non-harmonized soil classifications. An estimate of their uncertainty is also often missing. Thus, there are not easy to understand and often not properly used by end-users. Therefore, there is an urgent need to provide end-users with spatially exhaustive grids of essential soil properties, together with an estimate of their uncertainty. One way to achieve this is digital soil mapping (DSM). The concept of DSM relies on the hypothesis that soils and their properties are not randomly distributed, but that they depend on the main soil-forming factors that are climate, organisms, relief, parent material, time (age), and position in space. All these forming factors can be approximated using several exhaustive spatial products such as climatic grids, remote sensing products or vegetation maps, digital elevation models, geological or lithological maps, spatial coordinates of soil information, etc. Thus, DSM generally relies on models calibrated with existing observed soil data (point observations or maps) and so-called “ancillary co-variates” that come from other available spatial products. Then the model is generalized on grids where soil parameters are unknown in order to predict them, and the prediction performances are validated using various methods. With the growing demand for soil information at a national and global scale and the increase of available spatial co-variates national and continental DSM initiatives are continuously increasing. This short review illustrates the main national and continental advances in Europe, the diversity of the approaches and the databases that are used, the validation techniques and the main scientific and other issues. Examples from several countries illustrate the variety of products that were delivered during the last ten years. The scientific production on this topic is continuously increasing and new models and approaches are developed at an incredible speed. Most of the digital soil mapping (DSM) products rely mainly on machine learning (ML) prediction models and/or the use or pedotransfer functions (PTF) in which calibration data come from soil analyses performed in labs or for existing conventional maps. However, some scientific issues remain to be solved and also political and legal ones related, for instance, to data sharing and to different laws in different countries. Other issues related to communication to end-users and education, especially on the use of uncertainty. Overall, the progress is very important and the willingness of institutes and countries to join their efforts is increasing. Harmonization issues are still remaining, mainly due to differences in classifications or in laboratory standards between countries. However numerous initiatives are ongoing at the EU level and also at the global level. All these progress are scientifically stimulating and also promissing to provide tools to improve and monitor soil quality in countries, EU and at the global level.

Keywords: digital soil mapping, global soil mapping, national and European initiatives, global soil mapping products, mini-review

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Authors: Sidi Yang, Haiyi Zhang

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Twitter is a microblogging platform, where millions of users daily share their attitudes, views, and opinions. Using a probabilistic Latent Dirichlet Allocation (LDA) topic model to discern the most popular topics in the Twitter data is an effective way to analyze a large set of tweets to find a set of topics in a computationally efficient manner. Sentiment analysis provides an effective method to show the emotions and sentiments found in each tweet and an efficient way to summarize the results in a manner that is clearly understood. The primary goal of this paper is to explore text mining, extract and analyze useful information from unstructured text using two approaches: LDA topic modelling and sentiment analysis by examining Twitter plain text data in English. These two methods allow people to dig data more effectively and efficiently. LDA topic model and sentiment analysis can also be applied to provide insight views in business and scientific fields.

Keywords: text mining, Twitter, topic model, sentiment analysis

Procedia PDF Downloads 172

Authors: Afrah S. M. Al-Mahfadi

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Climate change is a global issue that has significant impacts on water resources, resulting in environmental, economic, and political consequences. Groundwater reserves, particularly in coastal areas, are facing depletion, leading to serious problems in regions such as Yemen. This study focuses on the western coastal region of Yemen, which already faces risks such as water crises, food insecurity, and widespread poverty. Climate change exacerbates these risks by causing high temperatures, sea level rise, inadequate sea level rise, and inadequate environmental policies. Research Aim: The aim of this research is to provide a comprehensive overview of the impact of climate change on the western coastal region of Yemen. Specifically, the study aims to analyze the relationship between climate change and the loss of fresh groundwater resources in this area. Methodology: The research utilizes a combination of a literature review and three case studies conducted through site visits. Arch-GIS mapping is employed to analyze and visualize the relationship between climate change and the depletion of fresh groundwater resources. Additionally, data on precipitation from 1981 to 2020 and scenarios of projected sea level rise (SLR) are considered. Findings: The study reveals several future issues resulting from climate change. It is projected that the annual temperature will increase while the rainfall rate will decrease. Furthermore, the sea level is expected to rise by approximately 0.30 to 0.72 meters by 2100. These factors contribute to the loss of wetlands, the retreat of shorelines and estuaries, and the intrusion of seawater into the coastal aquifer, rendering drinking water from wells increasingly saline. Data Collection and Analysis Procedures: Data for this research are collected through a literature review, including studies on climate change impacts in coastal areas and the hydrogeology of the study region. Furthermore, three case studies are conducted through site visits. Arch-GIS mapping techniques are utilized to analyze the relationship between climate change and the loss of fresh groundwater resources. Historical precipitation data from 1981 to 2020 and scenarios of projected sea level rise are also analyzed. Questions Addressed: (1) What is the impact of climate change on the western coastal region of Yemen? (2) How does climate change affect the availability of fresh groundwater resources in this area? Conclusion: The study concludes that the western coastal region of Yemen is facing significant challenges due to climate change. The projected increase in temperature, decrease in rainfall, and rise in sea levels have severe implications, such as the loss of wetlands, shorelines, and estuaries. Additionally, the intrusion of seawater into the coastal aquifer further exacerbates the issue of saline drinking water. Urgent measures are needed to address climate change, including improving water management, implementing integrated coastal zone planning, raising awareness among stakeholders, and implementing emergency projects to mitigate the impacts. Recommendations: To mitigate the adverse effects of climate change, several recommendations are provided. These include improving water management practices, developing integrated coastal zone planning strategies, raising awareness among all stakeholders, improving health and education, and implementing emergency projects to combat climate change. These measures aim to enhance adaptive capacity and resilience in the face of future climate change impacts.

Keywords: climate change, groundwater, coastal wetlands, Yemen

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Authors: Kwaku Damoah

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This paper presents a methodology and software application (App) designed to empower users in accessing, retrieving, and comparatively exploring data within the hierarchical network framework of the Government Finance Statistics (GFS) system. It explores the ease of navigating the GFS system and identifies the gaps filled by the new methodology and App. The GFS, embodies a complex Hierarchical Network Classification (HNC) structure, encapsulating institutional units, revenues, expenses, assets, liabilities, and economic activities. Navigating this structure demands specialized knowledge, experience, and skill, posing a significant challenge for effective analytics and fiscal policy decision-making. Many professionals encounter difficulties deciphering these classifications, hindering confident utilization of the system. This accessibility barrier obstructs a vast number of professionals, students, policymakers, and the public from leveraging the abundant data and information within the GFS. Leveraging R programming language, Data Science Analytics and Machine Learning, an efficient methodology enabling users to access, navigate, and conduct exploratory comparisons was developed. The machine learning Fiscal Analytics App (FLOWZZ) democratizes access to advanced analytics through its user-friendly interface, breaking down expertise barriers.

Keywords: data science, data wrangling, drilldown analytics, government finance statistics, hierarchical network classification, machine learning, web application.

Procedia PDF Downloads 59

Authors: Bremmy Laksono, Riksa Parikrama, Nur A. Rosyada, Willyanti Soewondo, Dadang S. H. Effendi, Eriska Rianti, Arlette S. Setiawan, Ine Sasmita, Risti S. Primanti, Erna Kurnikasari, Yunia Sribudiani

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Down syndrome (DS) is a chromosomal abnormality characterised by complete 21 chromosome trisomy (classical or non-disjunction), or partial 21 chromosome trisomy (mosaicism), or chromosome rearrangement involving chromosome 21 (translocation). This study was carried out to describe the frequency of DS patients in a research institution in the city of Bandung, Indonesia. This descriptive study also provides a picture of the residential location and surrounding area of their dwellings. This study involved people with DS in various age whose chromosome were evaluated by conventional karyotyping method and FISH. Data were collected from 60 patients with DS from a total 150 patients during the period of September 2015 to August 2016 who were referred to Cell Culture and Cytogenetics Laboratory, Faculty of Medicine Universitas Padjadjaran, Indonesia. Results showed that the most common type of DS was non-disjunction (93%), followed by mosaicism (5%), no patient with translocation DS (0%), and a very rare type of tetrasomy 21 (2%). There were 39 males (65%) and 21 females (35%) of DS patient. Most of them live in suburban area beyond Bandung city (55%) while the rest live inside urban area of Bandung city (45%). They live mostly in dense area of greater Bandung area (65%) and only a few live in mid-density area (25%) and the least live in sparse populated area (10%). Their houses are mostly located in residential estate area (55%), nearby industrial area (37%), and around agricultural area (8%). Based on the study, it could be concluded that non-disjunction DS is the most common type. DS patients referred to the laboratory mostly came from dense residential zone in suburban area outside Bandung city. The low number of DS patients referred to the laboratory for chromosome analysis was the highlight to improve health service for people with genetic disorder. This study offered several information regarding area of DS patients’ residence and the condition of neighbourhood in Bandung city where they live as well.

Keywords: chromosome, descriptive, Down syndrome, prevalence

Procedia PDF Downloads 271

Authors: Heiko Jessen, Laura Tanus, Slobodan Ruzicic

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Objectives: The efficacy of Stribild®, an integrase strand transfer inhibitor (INSTI) -based STR, has been evaluated in randomized clinical trials and it has demonstrated durable capability in terms of achieving sustained suppression of HIV-1 RNA-levels. However, differences in monitoring frequency, existing selection bias and profile of patients enrolled in the trials, may all result in divergent efficacy of this regimen in routine clinical settings. The aim of this study was to assess the virologic outcomes, safety and tolerability profile of Stribild® in a routine clinical setting. Methods: This was a retrospective monocentric analysis on HIV-1-infected patients, who started with or were switched to Stribild®. Virological failure (VF) was defined as confirmed HIV-RNA>50 copies/ml. The minimum time of follow-up was 24 weeks. The percentage of patients remaining free of therapeutic failure was estimated using the time-to-loss-of-virologic-response (TLOVR) algorithm, by intent-to-treat analysis. Results: We analyzed the data of 197 patients (56 ART-naïve and 141 treatment-experienced patients), who fulfilled the inclusion criteria. Majority (95.9%) of patients were male. The median time of HIV-infection at baseline was 2 months in treatment-naïve and 70 months in treatment-experienced patients. Median time [IQR] under ART in treatment-experienced patients was 37 months. Among the treatment-experienced patients 27.0% had already been treated with a regimen consisting of two NRTIs and one INSTI, whereas 18.4% of them experienced a VF. The median time [IQR] of virological suppression prior to therapy with Stribild® in the treatment-experienced patients was 10 months [0-27]. At the end of follow-up (median 33 months), 87.3% (95% CI, 83.5-91.2) of treatment-naïve and 80.3% (95% CI, 75.8-84.8) of treatment-experienced patients remained free of therapeutic failure. Considering only treatment-experienced patients with baseline VL<50 copies/ml, 83.0% (95% CI, 78.5-87.5) remained free of therapeutic failure. A total of 17 patients stopped treatment with Stribild®, 5.4% (3/56) of them were treatment-naïve and 9.9% (14/141) were treatment-experienced patients. The Stribild® therapy was discontinued in 2 (1.0%) because of VF, loss to follow-up in 4 (2.0%), and drug-drug interactions in 2 (1.0%) patients. Adverse events were in 7 (3.6%) patients the reason to switch from therapy with Stribild® and further 2 (1.0%) patients decided personally to switch. The most frequently observed adverse events were gastrointestinal side effects (20.0%), headache (8%), rash events (7%) and dizziness (6%). In two patients we observed an emergence of novel resistances in integrase-gene. The N155H evolved in one patient and resulted in VF. In another patient S119R evolved either during or shortly upon switch from therapy with Stribild®. In one further patient with VF two novel mutations in the RT-gene were observed when compared to historical genotypic test result (V106I/M and M184V), whereby it is not clear whether they evolved during or already before the switch to Stribild®. Conclusions: Effectiveness of Stribild® for treatment-naïve patients was consistent with data obtained in clinical trials. The safety and tolerability profile as well as resistance development confirmed clinical efficacy of Stribild® in a daily practice setting.

Keywords: ART, HIV, integrase inhibitor, stribild

Procedia PDF Downloads 281

Authors: Seonjae Lee, Sungjoo Lee

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Excavation is necessary to remain competitive in the current business environment. The company survived the rapidly changing industry conditions by adapting new business strategy and reducing technology challenges. Traditionally, the two methods are conducted excavations for new businesses. The first method is, qualitative analysis of expert opinion, which is gathered through opportunities and secondly, new technologies are discovered through quantitative data analysis of method patents. The second method increases time and cost. Patent data is restricted for use and the purpose of discovering business opportunities. This study presents the company's characteristics (sector, size, etc.), of new business opportunities in customized form by reviewing the value chain perspective and to contributing to creating new business opportunities in the proposed model. It utilizes the trademark database of the Korean Intellectual Property Office (KIPO) and proprietary company information database of the Korea Enterprise Data (KED). This data is key to discovering new business opportunities with analysis of competitors and advanced business trademarks (Module 1) and trading analysis of competitors found in the KED (Module 2).

Keywords: value chain, trademark, trading analysis, new business opportunity

Procedia PDF Downloads 366

Authors: Mousouris Spiridon, Kavakli Evangelia

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This paper focuses on Digital Libraries (DLs) that contain and geovisualise cultural data, highlighting the need to define them as a separate category termed Cultural Mapping Libraries, based on their inherent connection of culture with geographic location and their design requirements in support of visual representation of cultural data on the map. An exploratory analysis of DLs that conform to the above definition brought forward the observation that existing Cultural Mapping Libraries fail to geovisualise the entirety of cultural data per point of interest thus resulting in a Cultural Snapshot phenomenon. The existence of this phenomenon was reinforced by the results of a systematic bibliographic research. In order to address the Cultural Snapshot, this paper proposes the use of the Semantic Web principles to efficiently interconnect spatial cultural data through time, per geographic location. In this way points of interest are transformed into scenery where culture evolves over time. This evolution is expressed as occurrences taking place chronologically, in an event oriented approach, a conceptualization also endorsed by the CIDOC Conceptual Reference Model (CIDOC CRM). In particular, we posit the use of CIDOC CRM as the baseline for defining the logic of Cultural Mapping Libraries as part of the Culture Domain in accordance with the Digital Library Reference Model, in order to define the rules of cultural data management by the system. Our future goal is to transform this conceptual definition in to inferencing rules that resolve the Cultural Snapshot and lead to a more complete geovisualisation of cultural data.

Keywords: digital libraries, semantic web, geovisualization, CIDOC-CRM

Procedia PDF Downloads 97

Authors: Ibrahim Rabiu Darazo

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The research has been conducted on the impact of E-banking on the operational efficiency of Banks in Nigeria, A case of some selected banks (Diamond Bank Plc, GTBankPlc, and Fidelity Bank Plc) in Nigeria. The research is a quantitative research which uses both primary and secondary sources of data collection. Questionnaire were used to obtained accurate data, where 150 Questionnaire were distributed among staff and customers of the three Banks , and the data collected where analysed using chi-square, whereas the secondary data where obtained from relevant text books, journals and relevant web sites. It is clear from the findings that, the use of e-banking by the banks has improved the efficiency of these banks, in terms of providing efficient services to customers electronically, using Internet Banking, Telephone Banking ATMs, reducing time taking to serve customers, e-banking allow new customers to open an account online, customers have access to their account at all the time 24/7.E-banking provide access to customers information from the data base and cost of check and postage were eliminated using e-banking. The recommendation at the end of the research include; the Banks should try to update their electronic gadgets, e-fraud(internal & external) should also be controlled, Banks shall employ qualified man power, Biometric ATMs shall be introduce to reduce fraud using ATM Cards, as it is use in other countries like USA.

Keywords: banks, electronic banking, operational efficiency of banks, biometric ATMs

Procedia PDF Downloads 321

Authors: Shahira El Shafie, Hanaa Eldash, Engy Ghabbour, Mohamed Eid

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Several immunologic defects can be found in patients with beta-thalassemia, among which the impairment of neutrophil phagocytic function is of utmost importance. Attention has been directed to the role of proinflammatory cytokines in neutrophil chemotaxis and phagocytosis. Interleukin-8 (IL-8) is an important chemotactic and activation peptide for neutrophils; changes in IL-8 level and potential correlation with neutrophil function can be relevant to immunomodulation pathophysiology in beta-thalassemia patients. This case-control study aimed to evaluate IL-8 level and to assess granulocyte recruitment, as markers of immunomodulation, in poly-transfused thalassemia patients attending Fayoum University Hospitals. The study was conducted on 50 patients with ß thalassemia and 32 age-matched controls. 21/50 patients were transfused more than ten times, and 29/50 were transfused in a lower frequency. Patients and controls were subjected to thorough history taking and clinical examination, measurement of IL-8 level using human IL-8 ELISA kit, and Rebuck skin window technique (RSWT) to assess granulocyte recruitment. Our data showed statistically significant higher levels of IL-8 in ß thalassemia patients compared to control with a much higher difference in patients transfused more than ten times. Neutrophil recruitment was significantly lower in ß thalassemia patients compared to control at 4 hours and 24 hours test time. Although IL-8, the main chemotactic pro-inflammatory cytokine showed a higher level in thalassemia patients, neutrophils recruitment was significantly lower, especially in those receiving more than ten transfusion times. Our findings suggest a possible role of other neutrophil chemotactic factors, defective neutrophil response, or increased IL-8 as compensation of abnormal function. We recommend the use of IL-8 and Rebuck skin window technique as useful markers of immunomodulation in thalassemia and further study for these biomarkers to assess their clinical implications and impact on the management of thalassemia patients.

Keywords: beta-thalassemia, Interleukin-8, Rebuck skin window technique, immunomodulation

Procedia PDF Downloads 181