Search results for: data security

Authors: Rashmi Raghunandan, Sanjana Shankar, Rakshitha K. Bhat

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Social media contributes a vast amount of data and information about individuals to the internet. This project will greatly reduce the need for unnecessary manual analysis of large and diverse social media profiles by filtering out and combining the useful information from various social media profiles, eliminating irrelevant data. It differs from the existing social media aggregators in that it does not provide a consolidated view of various profiles. Instead, it provides consolidated INFORMATION derived from the subject’s posts and other activities. It also allows analysis over multiple profiles and analytics based on several profiles. We strive to provide a query system to provide a natural language answer to questions when a user does not wish to go through the entire profile. The information provided can be filtered according to the different use cases it is used for.

Keywords: social network, analysis, Facebook, Linkedin, git, big data

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Authors: Rima Shishakly, Mervyn Misajon

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Education is similar to other businesses and industries. Achieving data integrity is essential in order to attain a significant supporting for all the stakeholders in the educational sector. Efficient data collect, flow, processing, storing and retrieving are vital in order to deliver successful solutions to the different stakeholders. Ministry of Education (MOE) in United Arab Emirates (UAE) has adopted ‘Education 2020’ a series of five-year plans designed to introduce advanced education management information systems. As part of this program, in 2010 MOE implemented Student Information Systems (SIS) to manage and monitor the students’ data and information flow between MOE and international private schools in UAE. This paper is going to discuss data integrity concerns between MOE, and private schools. The paper will clarify the data integrity issues and will indicate the challenges that face private schools in UAE.

Keywords: education management information systems (EMIS), student information system (SIS), United Arab Emirates (UAE), ministry of education (MOE), (KHDA) the knowledge and human development authority, Abu Dhabi educational counsel (ADEC)

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Authors: Kamel Belammi, Houria Fatrim

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imbalanced data set, a problem often found in real world application, can cause seriously negative effect on classification performance of machine learning algorithms. There have been many attempts at dealing with classification of imbalanced data sets. In medical diagnosis classification, we often face the imbalanced number of data samples between the classes in which there are not enough samples in rare classes. In this paper, we proposed a learning method based on a cost sensitive extension of Least Mean Square (LMS) algorithm that penalizes errors of different samples with different weight and some rules of thumb to determine those weights. After the balancing phase, we applythe different classifiers (support vector machine (SVM), k- nearest neighbor (KNN) and multilayer neuronal networks (MNN)) for balanced data set. We have also compared the obtained results before and after balancing method.

Keywords: multilayer neural networks, k- nearest neighbor, support vector machine, imbalanced medical data, least mean square algorithm, diabetes

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Authors: Nael Hirzallah, Sana Nseir

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Merchants are competing to offer the use of mobile payment to encourage shopping. many mobile payment systems were made available in various locations worldwide; however, they have various drawbacks. This paper proposes a new mobile payment system that discusses the main drawbacks of these systems, namely security and speed of transaction. The proposal is featured by being simple to use by customers and merchants. Furthermore, the proposed system depends on a new authentication factor that is introduced in this paper and called by Two-Factors Authentication Plus, (2FA+).

Keywords: electronic commerce, payment schemes, mobile payment, authentication factors, mobile applications

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Authors: Evangelia-Matroni Tomara

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This thesis answers the question whether the media representations and reporting in 2015-2016 - especially, after the image of the drowned three-year-old Syrian boy in the Mediterranean Sea which made global headlines in the beginning of September 2015 -, the European Commission regulatory sources material and related reporting, have the power to challenge the conceptualization of humanitarianism or even redefine it. The theoretical foundations of the thesis are based on humanitarianism and its core definitions, the power of media representations and the relative portrayal of migrants, refugees and/or asylum seekers, as well as the dominant migration discourse and EU migration governance. Using content analysis for the media portrayal of migrants (436 newspaper articles) and qualitative content analysis for the European Commission Communication documents from May 2015 until June 2016 that required various depths of interpretation, this thesis allowed us to revise the concept of humanitarianism, realizing that the current crisis may seem to be a turning point for Europe but is not enough to overcome the past hostile media discourses and suppress the historical perspective of security and control-oriented EU migration policies. In particular, the crisis helped to shift the intensity of hostility and the persistence in the state-centric, border-oriented securitization in Europe into a narration of victimization rather than threat where mercy and charity dynamics are dominated and into operational mechanisms, noting the emergency of immediate management of the massive migrations flows, respectively. Although, the understanding of a rights-based response to the ongoing migration crisis, is being followed discursively in both political and media stage, the nexus described, points out that the binary between ‘us’ and ‘them’ still exists, with only difference that the ‘invaders’ are now ‘pathetic’ but still ‘invaders’. In this context, the migration crisis challenges the concept of humanitarianism because rights dignify migrants as individuals only in a discursive or secondary level while the humanitarian work is mostly related with the geopolitical and economic interests of the ‘savior’ states.

Keywords: European Union politics, humanitarianism, immigration, media representation, policy-making, refugees, security studies

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Authors: Eugenio Ferrer Santiago

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The growing complexities of the modern world on high-end gadgets, software applications, scams, identity theft, and Artificial Intelligence (AI) make the “uninformed” the weak and vulnerable to be victims of cybercrimes. Artificial Intelligence is not a new thing in our daily lives; the principles of database management, logical programming, and garbage in and garbage out are all connected to AI. The Philippines had in place legal safeguards against the abuse of cyberspace, but self-regulation of key industry players and self-protection by individuals are primordial to attain the success of these initiatives. Data protection, Data Privacy, and Research Ethics must work hand in hand during the policy process in the course of urban planning practice in different environments. This paper focuses on the interconnection of data protection, data privacy, and research ethics in coming up with clear-cut policies against perpetrators in the urban planning professional practice relevant in sustainable communities and smart cities. This paper shall use expository methodology under qualitative research using secondary data from related literature, interviews/blogs, and the World Wide Web resources. The claims and recommendations of this paper will help policymakers and implementers in the policy cycle. This paper shall contribute to the body of knowledge as a simple treatise and communication channel to the reading community and future researchers to validate the claims and start an intellectual discourse for better knowledge generation for the good of all in the near future.

Keywords: data privacy, data protection, urban planning, research ethics

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Authors: Abeer K. Jameel, Harry Evdorides

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Iraq is a middle income country where the road safety issue is considered one of the leading causes of deaths. To control the road risk issue, the Iraqi Ministry of Planning, General Statistical Organization started to organise a collection system of traffic accidents data with details related to their causes and severity. These data are published as an annual report. In this paper, a review of the available crash data in Iraq will be presented. The available data represent the rate of accidents in aggregated level and classified according to their types, road users’ details, and crash severity, type of vehicles, causes and number of causalities. The review is according to the types of models used in road safety studies and research, and according to the required road safety data in the road constructions tasks. The available data are also compared with the road safety dataset published in the United Kingdom as an example of developed country. It is concluded that the data in Iraq are suitable for descriptive and exploratory models, aggregated level comparison analysis, and evaluation and monitoring the progress of the overall traffic safety performance. However, important traffic safety studies require disaggregated level of data and details related to the factors of the likelihood of traffic crashes. Some studies require spatial geographic details such as the location of the accidents which is essential in ranking the roads according to their level of safety, and name the most dangerous roads in Iraq which requires tactic plan to control this issue. Global Road safety agencies interested in solve this problem in low and middle-income countries have designed road safety assessment methodologies which are basing on the road attributes data only. Therefore, in this research it is recommended to use one of these methodologies.

Keywords: road safety, Iraq, crash data, road risk assessment, The International Road Assessment Program (iRAP)

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Authors: Oluwole Durodolu

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The rationale for this study is to explore the adaptive strategy that librarians adopt in performing night shifts in a mega-city like Lagos state. Maslach Burnout Theory would be used to measure the three proportions of burnout in understanding emotional exhaustion, depersonalisation, and individual accomplishment to scrutinise job-related burnout syndrome allied with longstanding, unsolved stress. The qualitative methodology guided by a phenomenological research paradigm, which is an approach that focuses on the commonality of real-life experience in a particular group, would be used, focus group discussion adopted as a method of data collection from library staff who are involved in night-shift. The participant for the focus group discussion would be selected using a convenience sampling technique in which staff at the cataloguing unit would be included in the sample because of the representative characteristics of the unit. This would be done to enable readers to understand phenomena as it is reasonable than from a remote perspective. The exploratory interviews which will be in focus group method to shed light on issues relating to security, housing, transportation, budgeting, energy supply, employee duties, time management, information access, and sustaining professional levels of service and how all these variables affect the productivity of all the 149 library staff and their work-life balance.

Keywords: nightshift, work-life balance, mega-city, academic library, Maslach Burnout Theory, Lagos State, University of Lagos

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Authors: Sinead Impey, Damon Berry, Selma Furtado, Miriam Galvin, Loretto Grogan, Orla Hardiman, Lucy Hederman, Mark Heverin, Vincent Wade, Linda Douris, Declan O'Sullivan, Gaye Stephens

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Healthcare is a knowledge-rich environment. This knowledge, while valuable, is not always accessible outside the borders of individual clinics. This research aims to address part of this problem (at a study site) by constructing a maximal data set (knowledge artefact) for motor neurone disease (MND). This data set is proposed as an initial knowledge base for a concurrent project to develop an MND patient data platform. It represents the domain knowledge at the study site for the duration of the research (12 months). A knowledge elicitation method was also developed from the lessons learned during this process - the WICKED method. WICKED is an anagram of the words: eliciting and confirming data, information, knowledge, wisdom. But it is also a reference to the concept of wicked problems, which are complex and challenging, as is eliciting expert knowledge. The method was evaluated at a second site, and benefits and limitations were noted. Benefits include that the method provided a systematic way to manage data, information, knowledge and wisdom (DIKW) from various sources, including healthcare specialists and existing data sets. Limitations surrounded the time required and how the data set produced only represents DIKW known during the research period. Future work is underway to address these limitations.

Keywords: healthcare, knowledge acquisition, maximal data sets, action design science

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Authors: Payal Abichandani, Rishi Prakash, Paras Nath Barwal, B. K. Murthy

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Information generated from various computerization processes is a potential rich source of knowledge for its designated community. To pass this information from generation to generation without modifying the meaning is a challenging activity. To preserve and archive the data for future generations it’s very essential to prove the authenticity of the data. It can be achieved by extracting the metadata from the data which can prove the authenticity and create trust on the archived data. Subsequent challenge is the technology obsolescence. Metadata extraction and standardization can be effectively used to resolve and tackle this problem. Metadata can be categorized at two levels i.e. Technical and Domain level broadly. Technical metadata will provide the information that can be used to understand and interpret the data record, but only this level of metadata isn’t sufficient to create trustworthiness. We have developed a tool which will extract and standardize the technical as well as domain level metadata. This paper is about the different features of the tool and how we have developed this.

Keywords: digital preservation, metadata, OAIS, PDI, XML

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Authors: Antonio Gioiosa, Simone Doanti, Eric Flumerfelt, Luca Morescalchi, Elena Pedreschi, Gianantonio Pezzullo, Ryan A. Rivera, Franco Spinella

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The Mu2e experiment at Fermilab aims to measure the charged-lepton flavour violating neutrino-less conversion of a negative muon into an electron in the field of an aluminum nucleus. With the expected experimental sensitivity, Mu2e will improve the previous limit of four orders of magnitude. The Mu2e data acquisition (DAQ) system provides hardware and software to collect digitized data from the tracker, calorimeter, cosmic ray veto, and beam monitoring systems. Mu2e’s trigger and data acquisition system (TDAQ) uses otsdaq as its solution. developed at Fermilab, otsdaq uses the artdaq DAQ framework and art analysis framework, under-the-hood, for event transfer, filtering, and processing. Otsdaq is an online DAQ software suite with a focus on flexibility and scalability while providing a multi-user, web-based interface accessible through the Chrome or Firefox web browser. The detector read out controller (ROC) from the tracker and calorimeter stream out zero-suppressed data continuously to the data transfer controller (DTC). Data is then read over the PCIe bus to a software filter algorithm that selects events which are finally combined with the data flux that comes from a cosmic ray veto system (CRV).

Keywords: trigger, daq, mu2e, Fermilab

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Authors: Jiameng Wang, Yunfei Yin, Xiyu Deng

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Parallel optimization is one of the important research topics of data mining at this stage. Taking Classification and Regression Tree (CART) parallelization as an example, this paper proposes a parallel data mining algorithm based on SSP-OGini-PCCP. Aiming at the problem of choosing the best CART segmentation point, this paper designs an S-SP model without data association; and in order to calculate the Gini index efficiently, a parallel OGini calculation method is designed. In addition, in order to improve the efficiency of the pruning algorithm, a synchronous PCCP pruning strategy is proposed in this paper. In this paper, the optimal segmentation calculation, Gini index calculation, and pruning algorithm are studied in depth. These are important components of parallel data mining. By constructing a distributed cluster simulation system based on SPARK, data mining methods based on SSP-OGini-PCCP are tested. Experimental results show that this method can increase the search efficiency of the best segmentation point by an average of 89%, increase the search efficiency of the Gini segmentation index by 3853%, and increase the pruning efficiency by 146% on average; and as the size of the data set increases, the performance of the algorithm remains stable, which meets the requirements of contemporary massive data processing.

Keywords: classification, Gini index, parallel data mining, pruning ahead

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Authors: Meron Zenaselase Rata, Euridice Leyequien Abarca

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The production of major crops in Northern Ethiopia, especially the Tigray Region, is at subsistence level due to drought, erratic rainfall, and poor soil fertility. Since cactus pear is a drought-resistant plant, it is considered as a lifesaver fruit and a strategy for poverty reduction in a drought-affected area of the region. Despite its contribution to household income and food security in the area, the cactus pear sub-sector is experiencing many constraints with limited attention given to its post-harvest loss management. Therefore, this research was carried out to identify opportunities for reducing post-harvest losses and recommend possible strategies to reduce post-harvest losses, thereby improving production and smallholder’s income. Both probability and non-probability sampling techniques were employed to collect the data. Ganta Afeshum district was selected from Eastern Tigray, and two peasant associations (Buket and Golea) were also selected from the district purposively for being potential in cactus pear production. Simple random sampling techniques were employed to survey 30 households from each of the two peasant associations, and a semi-structured questionnaire was used as a tool for data collection. Moreover, in this research 2 collectors, 2 wholesalers, 1 processor, 3 retailers, 2 consumers were interviewed; and two focus group discussion was also done with 14 key farmers using semi-structured checklist; and key informant interview with governmental and non-governmental organizations were interviewed to gather more information about the cactus pear production, post-harvest losses, the strategies used to reduce the post-harvest losses and suggestions to improve the post-harvest management. To enter and analyze the quantitative data, SPSS version 20 was used, whereas MS-word were used to transcribe the qualitative data. The data were presented using frequency and descriptive tables and graphs. The data analysis was also done using a chain map, correlations, stakeholder matrix, and gross margin. Mean comparisons like ANOVA and t-test between variables were used. The analysis result shows that the present cactus pear value chain involves main actors and supporters. However, there is inadequate information flow and informal market linkages among actors in the cactus pear value chain. The farmer's gross margin is higher when they sell to the processor than sell to collectors. The significant postharvest loss in the cactus pear value chain is at the producer level, followed by wholesalers and retailers. The maximum and minimum volume of post-harvest losses at the producer level is 4212 and 240 kgs per season. The post-harvest loss was caused by limited farmers skill on-farm management and harvesting, low market price, limited market information, absence of producer organization, poor post-harvest handling, absence of cold storage, absence of collection centers, poor infrastructure, inadequate credit access, using traditional transportation system, absence of quality control, illegal traders, inadequate research and extension services and using inappropriate packaging material. Therefore, some of the recommendations were providing adequate practical training, forming producer organizations, and constructing collection centers.

Keywords: cactus pear, post-harvest losses, profit margin, value-chain

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Authors: Jindong Gu, Matthias Schubert, Volker Tresp

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In many outlier detection tasks, only training data belonging to one class, i.e., the positive class, is available. The task is then to predict a new data point as belonging either to the positive class or to the negative class, in which case the data point is considered an outlier. For this task, we propose a novel corrupted Generative Adversarial Network (CorGAN). In the adversarial process of training CorGAN, the Generator generates outlier samples for the negative class, and the Discriminator is trained to distinguish the positive training data from the generated negative data. The proposed framework is evaluated using an image dataset and a real-world network intrusion dataset. Our outlier-detection method achieves state-of-the-art performance on both tasks.

Keywords: one-class classification, outlier detection, generative adversary networks, semi-supervised learning

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Authors: Malay Bhattacharyya, Saparya Suresh

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The Correlation Structure associated with a portfolio is subjected to vary across time. Studying the structural breaks in the time-dependent Correlation matrix associated with a collection had been a subject of interest for a better understanding of the market movements, portfolio selection, etc. The current paper proposes a methodology for testing the change in the time-dependent correlation structure of a portfolio in the high dimensional data using the techniques of generalized inverse, singular valued decomposition and multivariate distribution theory which has not been addressed so far. The asymptotic properties of the proposed test are derived. Also, the performance and the validity of the method is tested on a real data set. The proposed test performs well for detecting the change in the dependence of global markets in the context of high dimensional data.

Keywords: correlation structure, high dimensional data, multivariate distribution theory, singular valued decomposition

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Authors: Jaheon Gu, Wooyong Chung, Mijung Koo, Seonbok Lee, Gyoutae Park, Sangguk Ahn, Hiesik Kim, Jungil Park

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In this paper, we present a portable ammonia gas detector for performing the gas safety management efficiently. The display of the detector is separated from its body. The display module is received the data measured from the detector using ZigBee. The detector has a rechargeable li-ion battery which can be use for 11~12 hours, and a Bluetooth module for sending the data to the PC or the smart devices. The data are sent to the server and can access using the web browser or mobile application. The range of the detection concentration is 0~100ppm.

Keywords: ammonia, detector, gas, portable

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Authors: Gichun Cha, Byoungjoon Yu, Jihwan Park, Minsoo Park, Junghyun Im, Sehwan Park, Sujung Sin, Seunghee Park

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The goal of this research is to estimate a structural shape change using terrestrial laser scanning. This study proceeds with development of data reduction and shape change estimation algorithm for large-capacity scan data. The point cloud of scan data was converted to voxel and sampled. Technique of shape estimation is studied to detect changes in structure patterns, such as skyscrapers, bridges, and tunnels based on large point cloud data. The point cloud analysis applies the octree data structure to speed up the post-processing process for change detection. The point cloud data is the relative representative value of shape information, and it used as a model for detecting point cloud changes in a data structure. Shape estimation model is to develop a technology that can detect not only normal but also immediate structural changes in the event of disasters such as earthquakes, typhoons, and fires, thereby preventing major accidents caused by aging and disasters. The study will be expected to improve the efficiency of structural health monitoring and maintenance.

Keywords: terrestrial laser scanning, point cloud, shape information model, displacement measurement

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Authors: Bodhayan Nandi, Shubhajit Roy Chowdhury

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This paper presents the development of a portable blood glucose monitoring device based on Near-Infrared Spectroscopy. The system supports Internet connectivity through WiFi and uploads the time series data of glucose concentration of patients to a server. In addition, the server is given sufficient intelligence to predict the future pathophysiological state of a patient given the current and past pathophysiological data. This will enable to prognosticate the approaching critical condition of the patient much before the critical condition actually occurs.The server hosts web applications to allow authorized users to monitor the data remotely.

Keywords: non invasive, blood glucose concentration, microcontroller, IoT, application server, database server

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Authors: Martin Juhas, Bohuslava Juhasova, Igor Halenar, Andrej Elias

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This article deals with the possibility of increasing efficiency, reliability and safety of the system for teledosimetric data collection management and their evaluation as a part of complex study for activity “Research of data collection, their measurement and evaluation with mobile and autonomous units” within project “Research of monitoring and evaluation of non-standard conditions in the area of nuclear power plants”. Possible weaknesses in existing system are identified. A study of available cluster solutions with possibility of their deploying to analysed system is presented.

Keywords: teledosimetric data, efficiency, reliability, safety, cluster solution

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Authors: Alessandra Pardu, Elena Curti, Marco Caredda, Alessio Dedola, Margherita Addis, Massimo Pes, Antonio Pirisi, Tonina Roggio, Sergio Uzzau, Roberto Anedda

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Some of the artisanal cheeses products of European Countries certificated as PDO (Protected Designation of Origin) are made from raw milk. To recognise potential frauds (e.g. pasteurisation or thermisation of milk aimed at raw milk cheese production), the alkaline phosphatase (ALP) assay is currently applied only for pasteurisation, although it is known to have notable limitations for the validation of ALP enzymatic state in nonbovine milk. It is known that frauds considerably impact on customers and certificating institutions, sometimes resulting in a damage of the product image and potential economic losses for cheesemaking producers. Robust, validated, and univocal analytical methods are therefore needed to allow Food Control and Security Organisms, to recognise a potential fraud. In an attempt to develop a new reliable method to overcome this issue, Time-Domain Nuclear Magnetic Resonance (TD-NMR) spectroscopy has been applied in the described work. Daily fresh milk was analysed raw (680.00 µL in each 10-mm NMR glass tube) at least in triplicate. Thermally treated samples were also produced, by putting each NMR tube of fresh raw milk in water pre-heated at temperatures from 68°C up to 72°C and for up to 3 min, with continuous agitation, and quench-cooled to 25°C in a water and ice solution. Raw and thermally treated samples were analysed in terms of 1H T2 transverse relaxation times with a CPMG sequence (Recycle Delay: 6 s, interpulse spacing: 0.05 ms, 8000 data points) and quasi-continuous distributions of T2 relaxation times were obtained by CONTIN analysis. In line with previous data collected by high field NMR techniques, a decrease in the spin-spin relaxation constant T2 of the predominant 1H population was detected in heat-treated milk as compared to raw milk. The decrease of T2 parameter is consistent with changes in chemical exchange and diffusive phenomena, likely associated to changes in milk protein (i.e. whey proteins and casein) arrangement promoted by heat treatment. Furthermore, experimental data suggest that molecular alterations are strictly dependent on the specific heat treatment conditions (temperature/time). Such molecular variations in milk, which are likely transferred to cheese during cheesemaking, highlight the possibility to extend the TD-NMR technique directly on cheese to develop a method for assessing a fraud related to the use of a milk thermal treatment in PDO raw milk cheese. Results suggest that TDNMR assays might pave a new way to the detailed characterisation of heat treatments of milk.

Keywords: cheese fraud, milk, pasteurisation, TD-NMR

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Authors: Bharat Singh Deora, Sushma Satpute

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Cloud computing is based on resource sharing. Like other resources which can be shareable, storage is a resource which can be shared. We can use collective resources of storage from different locations and maintain a central index table for storage details. The storage combining of different places can form a suitable data storage which is operated from one location and is very economical. Proper storage of data should improve data reliability & availability and bandwidth utilization. Also, we are moving the contents of one storage to other according to our need.

Keywords: cloud computing, cloud storage, Iaas, PaaS, SaaS

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Authors: T. Bryan , V. Kepuska, I. Kostnaic

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A method of data compression and denoising is introduced that is based on atomic decomposition of audio data using “basis vectors” that are learned from the audio data itself. The basis vectors are shown to have higher data compression and better signal-to-noise enhancement than the Gabor and gammatone “seed atoms” that were used to generate them. The basis vectors are the input weights of a Sparse AutoEncoder (SAE) that is trained using “envelope samples” of windowed segments of the audio data. The envelope samples are extracted from the audio data by performing atomic decomposition with Gabor or gammatone seed atoms. This process identifies segments of audio data that are locally coherent with the seed atoms. Envelope samples are extracted by identifying locally coherent audio data segments with Gabor or gammatone seed atoms, found by matching pursuit. The envelope samples are formed by taking the kronecker products of the atomic envelopes with the locally coherent data segments. Oracle signal-to-noise ratio (SNR) verses data compression curves are generated for the seed atoms as well as the basis vectors learned from Gabor and gammatone seed atoms. SNR data compression curves are generated for speech signals as well as early American music recordings. The basis vectors are shown to have higher denoising capability for data compression rates ranging from 90% to 99.84% for speech as well as music. Envelope samples are displayed as images by folding the time series into column vectors. This display method is used to compare of the output of the SAE with the envelope samples that produced them. The basis vectors are also displayed as images. Sparsity is shown to play an important role in producing the highest denoising basis vectors.

Keywords: sparse dictionary learning, autoencoder, sparse autoencoder, basis vectors, atomic decomposition, envelope sampling, envelope samples, Gabor, gammatone, matching pursuit

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Authors: A. Dudek, P. Tylec, G. Torbicz, P. Duda, K. Proniewska, P. Major, M. Pedziwiatr

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Background: Conservative treatments of obesity, based only on a proper diet and physical activity, without the support of an interdisciplinary team of specialist does not bring satisfactory bariatric results. Long-term maintenance of a proper metabolic results after rapid weight loss due to bariatric surgery requires engagement from patients. Mobile health tool may offer alternative model that enhance participant engagement in keeping the therapy. Objective: We aimed to assess the influence of constant monitoring and subsequent motivational alerts in perioperative period and on post-operative effects in the bariatric patients. As well as the study was designed to identify factors conductive urge to change lifestyle after surgery. Methods: This prospective clinical control study was based on a usage of a designed prototype of bariatric mHealth system. The prepared application comprises central data management with a comprehensible interface dedicated for patients and data transfer module as a physician’s platform. Motivation system of a platform consist of motivational alerts, graphic outcome presentation, and patient communication center. Generated list of patients requiring urgent consultation and possibility of a constant contact with a specialist provide safety zone. 31 patients were enrolled in continuous monitoring program during a 6-month period along with typical follow-up visits. After one year follow-up, all patients were examined. Results: There were 20 active users of the proposed monitoring system during the entire duration of the study. After six months, 24 patients took a part in a control by telephone questionnaires. Among them, 75% confirmed that the application concept was an important element in the treatment. Active users of the application indicated as the most valuable features: motivation to continue treatment (11 users), graphical presentation of weight loss, and other parameters (7 users), the ability to contact a doctor (3 users). The three main drawbacks are technical errors (9 users), tedious questionnaires inside the application (5 users), and time-consuming tasks inside the system (2 users). Conclusions: Constant monitoring and successive motivational alerts to continue treatment is an appropriate tool in the treatment after bariatric surgery, mainly in the early post-operative period. Graphic presentation of data and continuous connection with a clinical staff seemed to be an element of motivation to continue treatment and a sense of security.

Keywords: bariatric surgery, mHealth, mobile health tool, obesity

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Authors: Maha Shamseddine, Amjad Nusayr, Wassim Itani

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In this paper, we present a Platform-as-a-Service (PaaS) model for controlling the privacy enforcement mechanisms applied on user data when stored and processed in Cloud data centers. The proposed architecture consists of establishing user configurable ‘sticky’ policies on the Graphical User Interface (GUI) data-bound components during the application development phase to specify the details of privacy enforcement on the contents of these components. Various privacy classification classes on the data components are formally defined to give the user full control on the degree and scope of privacy enforcement including the type of execution containers to process the data in the Cloud. This not only enhances the privacy-awareness of the developed Cloud services, but also results in major savings in performance and energy efficiency due to the fact that the privacy mechanisms are solely applied on sensitive data units and not on all the user content. The proposed design is implemented in a real PaaS cloud computing environment on the Microsoft Azure platform.

Keywords: privacy enforcement, platform-as-a-service privacy awareness, cloud computing privacy

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Authors: Arth J. Shah, Madhu R. Kamble

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Voice biometric liveness detection is customized to certify an authentication process of the voice data presented is genuine and not a recording or synthetic voice. With the rise of deepfakes and other equivalently sophisticated spoofing generation techniques, it’s becoming challenging to ensure that the person on the other end is a live speaker or not. Voice Liveness Detection (VLD) system is a group of security measures which detect and prevent voice spoofing attacks. Motivated by the recent development of the Kolmogorov-Arnold Network (KAN) based on the Kolmogorov-Arnold theorem, we proposed KAN for the VLD task. To date, multilayer perceptron (MLP) based classifiers have been used for the classification tasks. We aim to capture not only the compositional structure of the model but also to optimize the values of univariate functions. This study explains the mathematical as well as experimental analysis of KAN for VLD tasks, thereby opening a new perspective for scientists to work on speech and signal processing-based tasks. This study emerges as a combination of traditional signal processing tasks and new deep learning models, which further proved to be a better combination for VLD tasks. The experiments are performed on the POCO and ASVSpoof 2017 V2 database. We used Constant Q-transform, Mel, and short-time Fourier transform (STFT) based front-end features and used CNN, BiLSTM, and KAN as back-end classifiers. The best accuracy is 91.26 % on the POCO database using STFT features with the KAN classifier. In the ASVSpoof 2017 V2 database, the lowest EER we obtained was 26.42 %, using CQT features and KAN as a classifier.

Keywords: Kolmogorov Arnold networks, multilayer perceptron, pop noise, voice liveness detection

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Authors: Mike Chia-Yu Huang

Abstract:

China’s port facility construction projects in the Indian Ocean (IO) region, Gwadar Port and Djibouti Port projects in particular, have led to a heated debate among both Chinese and Western strategists over whether the country has literally been carrying out its “string of pearls” strategy, an alleged Chinese plan to challenge America’s military predominance in South Asia. Even though the Chinese government repeatedly denied the existence of such a strategy and highlighted the civilian/commercial nature of its port projects, it has significantly enhanced its strategic cooperation with littoral countries in the IO region since the “One Belt One Road” initiative was introduced by Chinese President Xi Jinping in 2013. Whether China does have a plan to expand its sphere of military influence westward concerns the balance of power in the IO region. If the answer is positive, the security environment there will be changed drastically. This paper argues that rather than simply copying the U.S. model of developing overseas military bases along the IO periphery, Beijing has been deliberating a more sophisticated plan for its physical presence there: creating a new set of “overseas strategic pivots.” These “pivots,” semi-military and semi-commercial in nature, are designed to help Beijing sustain its anti-piracy operations in the Gulf of Aden and serve as forward stations for the transportation of China’s imported energy and merchandise. They can support the Chinese Navy’s operations overseas but are not supposed to undertake face-to-face combat missions. This upgraded Chinese scheme can be identified as “string of pearls” strategy 2.0. Moreover, it is expected to help China deepen its roots in the IO region, implying that Beijing has to a large extent scratched its old diplomatic philosophy which highlighted the merits of non-interference and nonalignment. While a full-scale maritime confrontation between China and the U.S.-India security alliance is unlikely to be witnessed in the near future, an ambitious Chinese plan to step into the global maritime domain has been evidently shown.

Keywords: Chinese navy, Djibouti, Gwadar, Indian Ocean, string of pearls strategy

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Authors: María Dolores Caro, Eugenio M. Fedriani, Ángel F. Tenorio

Abstract:

When lorries transport dangerous goods, there exist some legal stipulations in the European Union for assuring the security of the rest of road users as well as of those goods being transported. At this respect, lorry drivers cannot park in usual parking areas, because they must use parking areas with special conditions, including permanent supervision of security personnel. Moreover, drivers are compelled to satisfy additional regulations about resting and driving times, which involve in the practical possibility of reaching the suitable parking areas under these time parameters. The “European Agreement concerning the International Carriage of Dangerous Goods by Road” (ADR) is the basic regulation on transportation of dangerous goods imposed under the recommendations of the United Nations Economic Commission for Europe. Indeed, nowadays there are no enough parking areas adapted for dangerous goods and no complete study have suggested the best locations to build new areas or to adapt others already existing to provide the areas being necessary so that lorry drivers can follow all the regulations. The goal of this paper is to show how many additional parking areas should be built in the Iberian Peninsula to allow that lorry drivers may park in such areas under their restrictions in resting and driving time. To do so, we have modeled the problem via graph theory and we have applied a new efficient algorithm which determines an optimal solution for the problem of locating new parking areas to complement those already existing in the ADR for the Iberian Peninsula. The solution can be considered minimal since the number of additional parking areas returned by the algorithm is minimal in quantity. Obviously, graph theory is a natural way to model and solve the problem here proposed because we have considered as nodes: the already-existing parking areas, the loading-and-unloading locations and the bifurcations of roads; while each edge between two nodes represents the existence of a road between both nodes (the distance between nodes is the edge's weight). Except for bifurcations, all the nodes correspond to parking areas already existing and, hence, the problem corresponds to determining the additional nodes in the graph such that there are less up to 100 km between two nodes representing parking areas. (maximal distance allowed by the European regulations).

Keywords: dangerous goods, parking areas, Iberian peninsula, graph-based modeling

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Authors: Ahmad Alsaber

Abstract:

This paper aims to understand the intermediary role of the payment platform applications by analyzing the various factors that can influence the desirability of utilizing said payment services in Kuwait, as well as to determine the effect of the presence of different types of payment platforms on the variables of the “Unified Theory of Acceptance and Use of Technology” (UTAUT) model. The UTAUT model's findings will provide an important understanding of the moderating role of payment platform mobile applications. This study will explore the influence of payment platform mobile applications on customer purchase intentions in Kuwait by employing a quantitative survey of 200 local customers. Questions will cover their usage of payment platforms, purchase intent, and overall satisfaction. The information gathered is then analyzed using descriptive statistics and correlation analysis in order to gain insights. The research hopes to provide greater insight into the effect of mobile payment platforms on customer purchase intentions in Kuwait. This research will provide important implications to marketers and customer service providers, informing their strategies and initiatives, as well as offer recommendations to payment platform providers on how to improve customer satisfaction and security. The study results suggest that the likelihood of a purchase is affected by performance expectancy, effort expectancy, social influence, risk, and trust. The purpose of this research is to understand the advancements in the different variables that Kuwaiti customers consider while dealing with mobile banking applications. With the implementation of stronger security measures, progressively more payment platform applications are being utilized in the Kuwaiti marketplace, making them more desirable with their accessibility and usability. With the development of the Kuwaiti digital economy, it is expected that mobile banking will have a greater impact on banking transactions and services in the future.

Keywords: purchase intention, UTAUT, performance expectancy, social influence, risk, trust

Procedia PDF Downloads 117

Authors: Saurav Kumar Suman, P. Karthigayani

Abstract:

In this paper the height of the tree is estimated and forest types is classified from the multi temporal RISAT-1 Horizontal-Horizontal (HH) and Horizontal-Vertical (HV) Polarised Satellite Aperture Radar (SAR) data. The novelty of the proposed project is combined use of the Back-scattering Coefficients (Sigma Naught) and the Coherence. It uses Water Cloud Model (WCM). The approaches use two main steps. (a) Extraction of the different forest parameter data from the Product.xml, BAND-META file and from Grid-xxx.txt file come with the HH & HV polarized data from the ISRO (Indian Space Research Centre). These file contains the required parameter during height estimation. (b) Calculation of the Vegetation and Ground Backscattering, Coherence and other Forest Parameters. (c) Classification of Forest Types using the ENVI 5.0 Tool and ROI (Region of Interest) calculation.

Keywords: RISAT-1, classification, forest, SAR data

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Authors: Ruhizal Roosli, Julaihi Wahid, Abu Hassan Abu Bakar, Faizal Baharum

Abstract:

This paper reports on the progress of a study on the reconstruction project after the ‘Yellow Flood’ disaster in Kelantan, Malaysia. Malaysia still does not have guidelines to build housing after a disaster especially in disaster-prone areas. At the international level, many guidelines have been prepared that is found suitable for post-disaster housing. Which guidelines can be adapted that best describes the situation in Malaysia? It was reported that the houses should be built on stilts, which can withstand certain level of impact during flooding. Unfortunately, until today no specific guideline was available to assist homeowners to rebuild their homes after disaster. In addition, there is also no clear operational procedure to monitor the progress of this construction work. This research is an effort to promoting resilient housing; safety and security; and secure tenure in a prone area. At the end of this study, key lessons will be emerged from the review process and data analysis. These inputs will then have influenced to the content that will be developed and presented as guidelines. An overall objective is to support humanitarian responses to disaster and conflicts for resilience house construction to flood prone area. Interviews with the field based staff were from recent post-disaster housing workforce (disaster management mechanism in Malaysia especially in Kelantan). The respondents were selected based on their experiences in disaster response particularly related to housing provision. These key lessons are perhaps the best practical (operational and technical) guidelines comparing to other International cases to be adapted to the national situations.

Keywords: disaster, guideline, housing, Malaysia, reconstruction

Procedia PDF Downloads 521