Search results for: minimum data set

Authors: Pankhudi Khandelwal

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The revenue models of digital giants such as Facebook and Google, use targeted advertising for revenues. Such a model requires huge amounts of consumer data. While the data protection law deals with the protection of personal data, however, this data is acquired by the companies on the basis of consent, performance of a contract, or legitimate interests. This paper analyses the role that competition law can play in evading these loopholes for the protection of data and privacy of online consumers. Digital markets have certain distinctive features such as network effects and feedback loop, which gives incumbents of these markets a first-mover advantage. This creates a situation where the winner takes it all, thus creating entry barriers and concentration in the market. It has been also seen that this dominant position is then used by the undertakings for leveraging in other markets. This can be harmful to the consumers in form of less privacy, less choice, and stifling innovation, as seen in the cases of Facebook Cambridge Analytica, Google Shopping, and Google Android. Therefore, the article aims to provide a legal framework wherein the data protection law and competition law can come together to provide a balance in regulating digital markets. The issue has become more relevant in light of the Facebook decision by German competition authority, where it was held that Facebook had abused its dominant position by not complying with data protection rules, which constituted an exploitative practice. The paper looks into the jurisdictional boundaries that the data protection and competition authorities can work from and suggests ex ante regulation through data protection law and ex post regulation through competition law. It further suggests a change in the consumer welfare standard where harm to privacy should be considered as an indicator of low quality.

Keywords: data protection, dominance, ex ante regulation, ex post regulation

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Authors: Mai Ghazal, Ahmed Hammad

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Cost overruns in construction projects are considered as worldwide challenges since the cost performance is one of the main measures of success along with schedule performance. To overcome this problem, studies were conducted to investigate the cost overruns' factors, also projects' historical data were analyzed to extract new and useful knowledge from it. This research is studying and analyzing the effect of some factors causing cost overruns using the historical data from completed construction projects. Then, using these factors to estimate the probability of cost overrun occurrence and predict its percentage for future projects. First, an intensive literature review was done to study all the factors that cause cost overrun in construction projects, then another review was done for previous researcher papers about mining process in dealing with cost overruns. Second, a proposed data warehouse was structured which can be used by organizations to store their future data in a well-organized way so it can be easily analyzed later. Third twelve quantitative factors which their data are frequently available at construction projects were selected to be the analyzed factors and suggested predictors for the proposed model.

Keywords: construction management, construction projects, cost overrun, cost performance, data mining, data warehousing, knowledge discovery, knowledge management

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Authors: Temiloluwa J. Akinyemi, Denis W. Aheto, Wisdom Akpalu

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Capture fisheries in developing countries provide significant animal protein and directly supports the livelihoods of several communities. However, the misperception of biophysical dynamics owing to a lack of adequate scientific data has contributed to the suboptimal management in marine capture fisheries. This is because yield and catch potentials are sensitive to the quality of catch and effort data. Yet, studies on fisheries data collection practices in developing countries are hard to find. This study investigates the data collection methods utilized by fisheries technical officers within the four fishing regions of Ghana. We found that the officers employed data collection and sampling procedures which were not consistent with the technical guidelines curated by FAO. For example, 50 instead of 166 landing sites were sampled, while 290 instead of 372 canoes were sampled. We argue that such sampling errors could result in the over-capitalization of capture fish stocks and significant losses in resource rents.

Keywords: Fisheries data quality, fisheries management, Ghana, Sustainable Fisheries

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Authors: Helen Huang, Francisco Javier Quesada Ocet, Blanca Quesada Oce, Javier Jimenez Bello, Victor Palanca Gil, Alba Cervero Rubio, Ana Paya Chaume, Alejandro Herreros-Pomares, Fernando Vidal-Vanaclocha, Rafael Paya Serrano, Aurelio Quesada Dorador, Monica Soliman

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Background: Cancer favors both the pro-inflammatory state and autonomic dysfunction, two important mechanisms in the genesis of AF. Atrial remodeling might be caused as a result of paraneoplastic conditions or the result of direct expression of neoplasia. Here, we hypothesize that cancer, through inflammatory mediators, may favor the appearance of AF and patients with the first episode of AF could have a higher risk of developing cancer. Method: Data was collected from patients who attended the emergency department of our hospital for the first episode of AF, diagnosed electrocardiographically, between 2010-2015 (n = 712). The minimum follow-up was 2 years, recording the appearance of cancer, total mortality, recurrences of AF and other events. Patients who developed cancer and those who did not during the 2 years after the onset of AF were compared, as well as with the incidence of cancer in Spain in 2012. Results: After 2 years, 35 patients (4.91%) were diagnosed with cancer, with an annual incidence of 2.45%. Hematological neoplasms were the most frequent (34.28%). The cancer group was older (76.68 +/-12.75 years vs 74.16 +/-12.71; p <0.05) and had fewer typical symptoms (palpitations) (33.38% vs 14.28% , p <0.05). The incidence of cancer in Spain during 2012 was 0.46%, much lower than our sample. When comparing the incidence by age, these differences were maintained both in those over 65 years of age and in those under 65 years of age (2.17% vs. 0.28%; 0.28% vs. 0.18% respectively). Discussion: Therefore, a high incidence of cancer in patients with the first episode of AF was observed (the annual incidence of 2.45% after the onset of AF is 6.1 times that of the general population). After the evaluation of patients with AF in their first detected episode, surveillance of the appearance of cancer should be considered in clinical practice.

Keywords: cancer, cardiovascular outcomes, atrial fibrillation, inflammation

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Authors: Afroza Parvin, Md. Mahmudul Hasan, Md. Rokunozzaman, Papon Debnath

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The effluents of textile industries have considerable amounts of heavy metals, causing potential microbial metal loads if discharged into the environment without treatment. Aim: In this present study, both lactose and non-lactose fermenting bacterial isolates were isolated from textile industrial effluents of a specific region of Bangladesh, named Savar, to compare and understand the load of heavy metals in these microorganisms determining the effects of heavy metal resistance properties on antibiotic resistance. Methods: Five different textile industrial canals of Savar were selected, and effluent samples were collected in 2016 between June to August. Total bacterial colony (TBC) was counted for day 1 to day 5 for 10-6 dilution of samples to 10-10 dilution. All the isolates were isolated and selected using 4 differential media, and tested for the determination of minimum inhibitory concentration (MIC) of heavy metals and antibiotic susceptibility test with plate assay method and modified Kirby-Bauer disc diffusion method, respectively. To detect the combined effect of heavy metals and antibiotics, a binary exposure experiment was performed, and to understand the plasmid profiling plasmid DNA was extracted by alkaline lysis method of some selective isolates. Results: Most of the cases, the colony forming units (CFU) per plate for 50 ul diluted sample were uncountable at 10-6 dilution, however, countable for 10-10 dilution and it didn’t vary much from canal to canal. A total of 50 Shigella, 50 Salmonella, and 100 E.coli (Escherichia coli) like bacterial isolates were selected for this study where the MIC was less than or equal to 0.6 mM for 100% Shigella and Salmonella like isolates, however, only 3% E. coli like isolates had the same MIC for nickel (Ni). The MIC for chromium (Cr) was less than or equal to 2.0 mM for 16% Shigella, 20% Salmonella, and 17% E. coli like isolates. Around 60% of both Shigella and Salmonella, but only 20% of E.coli like isolates had a MIC of less than or equal to 1.2 mM for lead (Pb). The most prevalent resistant pattern for azithromycin (AZM) for Shigella and Salmonella like isolates was found 38% and 48%, respectively; however, for E.coli like isolates, the highest pattern (36%) was found for sulfamethoxazole-trimethoprim (SXT). In the binary exposure experiment, antibiotic zone of inhibition was mostly increased in the presence of heavy metals for all types of isolates. The highest sized plasmid was found 21 Kb and 14 Kb for lactose and non-lactose fermenting isolates, respectively. Conclusion: Microbial resistance to antibiotics and metal ions, has potential health hazards because these traits are generally associated with transmissible plasmids. Microorganisms resistant to antibiotics and tolerant to metals appear as a result of exposure to metal-contaminated environments.

Keywords: antibiotics, effluents, heavy metals, minimum inhibitory concentration, resistance

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Authors: Khaled Ahmed Kadouh, Kamal Ali Albashiri

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This paper presents a designed algorithm involves improvement of transferring data over Simple Object Access Protocol (SOAP). The aim of this work is to establish whether using SOAP in exchanging XML messages has any added advantages or not. The results showed that XML messages without SOAP take longer time and consume more memory, especially with binary data.

Keywords: JAX-WS, SMTP, SOAP, web service, XML

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Authors: Joseph Udofia, Isaac Olufadewa

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Everyday, the size of Electronic Health Records data keeps increasing as new patients visit health practitioner and returning patients fulfil their appointments. As these data grow, so is their susceptibility to cyber-attacks from criminals waiting to exploit this data. In the US, the damages for cyberattacks were estimated at $8 billion (2018), $11.5 billion (2019) and $20 billion (2021). These attacks usually involve the exposure of PII. Health data is considered PII, and its exposure carry significant impact. To this end, an enhancement of Health Policy and Standards in relation to data security, especially among patients and their clinical providers, is critical to ensure ethical practices, confidentiality, and trust in the healthcare system. As Clinical accelerators and applications that contain user data are used, it is expedient to have a review and revamp of policies like the Payment Card Industry Data Security Standard (PCI DSS), the Health Insurance Portability and Accountability Act (HIPAA), the Fast Healthcare Interoperability Resources (FHIR), all aimed to ensure data protection and security in healthcare. FHIR caters for healthcare data interoperability, FHIR caters to healthcare data interoperability, as data is being shared across different systems from customers to health insurance and care providers. The astronomical cost of implementation has deterred players in the space from ensuring compliance, leading to susceptibility to data exfiltration and data loss on the security accuracy of protected health information (PHI). Though HIPAA hones in on the security accuracy of protected health information (PHI) and PCI DSS on the security of payment card data, they intersect with the shared goal of protecting sensitive information in line with industry standards. With advancements in tech and the emergence of new technology, it is necessary to revamp these policies to address the complexity and ambiguity, cost barrier, and ever-increasing threats in cyberspace. Healthcare data in the wrong hands is a recipe for disaster, and we must enhance its protection and security to protect the mental health of the current and future generations.

Keywords: cloud security, healthcare, cybersecurity, policy and standard

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Authors: Peristera Baziana

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In this paper, we present a network configuration for a WDM LANs of passive star topology that assume that the set of data WDM channels is split into two separate sets of channels, with different access rights over them. Especially, a synchronous transmission WDMA access algorithm is adopted in order to increase the probability of successful transmission over the data channels and consequently to reduce the probability of data packets transmission cancellation in order to avoid the data channels collisions. Thus, a control pre-transmission access scheme is followed over a separate control channel. An analytical Markovian model is studied and the average throughput is mathematically derived. The performance is studied for several numbers of data channels and various values of control phase duration.

Keywords: access algorithm, channels division, collisions avoidance, wavelength division multiplexing

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Authors: D. I. George Amalarethinam, A. Emima

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Educational Data Mining (EDM) is one of the newest topics to emerge in recent years, and it is concerned with developing methods for analyzing various types of data gathered from the educational circle. EDM methods and techniques with machine learning algorithms are used to extract meaningful and usable information from huge databases. For scientists and researchers, realistic applications of Machine Learning in the EDM sectors offer new frontiers and present new problems. One of the most important research areas in EDM is predicting student success. The prediction algorithms and techniques must be developed to forecast students' performance, which aids the tutor, institution to boost the level of student’s performance. This paper examines various classification techniques in prediction methods and data mining tools used in EDM.

Keywords: classification technique, data mining, EDM methods, prediction methods

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Authors: Yadwinder Kumar, Priyanka Rani Amandeep Singh

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In this paper the design of a multiband pre-fractal micro strip antenna with proximity coupling feed is presented. The proposed antenna resonates on seven different frequencies that are 2.6 GHz, 5.1 GHz, 9.4 GHz, 11.5 GHz, 13.8 GHz, 16.3 GHz, and 18.6 GHz. Simulated results presented here shows that the minimum return loss is achieved at the 16.3 GHz frequency which is up to 37 dB. Also the maximum band width of 700 MHz is achieved by the frequency bands 13.4 GHz to 14.1 GHz, 15.9 GHz to 16.6 GHz and 18.2 GHz to 18.9 GHz. The proposed feed line is sandwiched between two substrate layers and increases in the bandwidth of antenna has been observed up to 13% in comparison of micro strip feed line. Effect of key design parameters such as variation in substrate material, substrate height and feeding technique on antenna S-parameter have been investigated and discussed.

Keywords: fractal antenna, pre-fractals, micro strip antenna, ISM band, electromagnetic coupling, VSWR

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Authors: Aofan Liu, Qianqian Tan, Burra Venkata Durga Kumar

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Data security is of the utmost importance in the healthcare area, as sensitive patient information is constantly sent around and analyzed by many different parties. The use of federated learning, which enables data to be evaluated locally on devices rather than being transferred to a central server, has emerged as a potential solution for protecting the privacy of user information. To protect against data breaches and unauthorized access, federated learning alone might not be adequate. In this context, the application of blockchain technology could provide the system extra protection. This study proposes a distributed federated learning system that is built on blockchain technology in order to enhance security in healthcare. This makes it possible for a wide variety of healthcare providers to work together on data analysis without raising concerns about the confidentiality of the data. The technical aspects of the system, including as the design and implementation of distributed learning algorithms, consensus mechanisms, and smart contracts, are also investigated as part of this process. The technique that was offered is a workable alternative that addresses concerns about the safety of healthcare while also fostering collaborative research and the interchange of data.

Keywords: data privacy, distributed system, federated learning, machine learning

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Authors: Akshay Agrawal, Anand K. Srivastava

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The increasing amount of XML datasets available to casual users increases the necessity of investigating techniques to extract knowledge from these data. Data mining is widely applied in the database research area in order to extract frequent correlations of values from both structured and semi-structured datasets. The increasing availability of heterogeneous XML sources has raised a number of issues concerning how to represent and manage these semi structured data. In recent years due to the importance of managing these resources and extracting knowledge from them, lots of methods have been proposed in order to represent and cluster them in different ways.

Keywords: XML, similarity measure, clustering, cluster quality, semantic clustering

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Authors: Hiesik Kim, YongBeum Kim

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Internet of Things (IoT) applications are widely serviced and spread worldwide. Local wireless data transmission technique must be developed to speed up with some technique. Bluetooth wireless data communication is wireless technique is technique made by Special Inter Group(SIG) using the frequency range 2.4 GHz, and it is exploiting Frequency Hopping to avoid collision with different device. To implement experiment, equipment for experiment transmitting measured data is made by using Arduino as Open source hardware, Gas sensor, and Bluetooth Module and algorithm controlling transmission speed is demonstrated. Experiment controlling transmission speed also is progressed by developing Android Application receiving measured data, and controlling this speed is available at the experiment result. it is important that in the future, improvement for communication algorithm be needed because few error occurs when data is transferred or received.

Keywords: Arduino, Bluetooth, gas sensor, internet of things, transmission Speed

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Authors: Sreejith Gopinath, Aspen Olmsted

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This paper is based on our previous work that proposed a risk-transference-based architecture for healthcare systems to store sensitive data outside the system boundary, rendering the system unattractive to would-be bad actors. This architecture also allows a compromised system to be abandoned and a new system instance spun up in place to ensure business continuity without paying a ransom or engaging with a bad actor. This paper delves into the details of various attacks we simulated against the prototype system. In the paper, we discuss at length the time and computational costs associated with storing and retrieving data in the prototype system, abandoning a compromised system, and setting up a new instance with existing data. Lastly, we simulate some analytical workloads over the data stored in our specialized data storage system and discuss the time and computational costs associated with running analytics over data in a specialized storage system outside the system boundary. In summary, this paper discusses the total costs of data storage, access, and analytics incurred with the proposed architecture.

Keywords: cybersecurity, healthcare, ransomware, resilience, risk transference

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Authors: Ismayanti Magfirah, Sartohadi Junun, Samodra Guruh

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Landslides are one of the most frequent and devastating natural disasters in Indonesia. Many studies have been conducted regarding this phenomenon. However, there is a lack of attention in the landslide inventory mapping. The natural condition (dense forest area) and the limited human and economic resources are some of the major problems in building landslide inventory in Indonesia. Considering the importance of landslide inventory data in susceptibility, hazard, and risk analysis, it is essential to generate landslide inventory based on available resources. In order to achieve this, the first thing we have to do is identify the landslides' location. The presence of Sentinel-1A and Sentinel-2A data gives new insights into land monitoring investigation. The free access, high spatial resolution, and short revisit time, make the data become one of the most trending open sources data used in landslide mapping. Sentinel-1A and Sentinel-2A data have been used broadly for landslide detection and landuse/landcover mapping. This study aims to generate landslide map by integrating Sentinel-1A and Sentinel-2A data use change detection method. The result will be validated by field investigation to make preliminary landslide inventory in the study area.

Keywords: change detection method, landslide inventory mapping, Sentinel-1A, Sentinel-2A

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Authors: Mojtaba Hakimi-Moghaddam

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Routh-Hurwitz stability criterion is a powerful approach to determine stability of linear time invariant systems. On the other hand, applying this criterion to characteristic equation of a system, whose stability or marginal stability can be determined. Although the command roots (.) of MATLAB software can be easily used to determine the roots of a polynomial, the characteristic equation of closed loop system usually includes parameters, so software cannot handle it; however, Routh-Hurwitz stability criterion results the region of parameter changes where the stability is guaranteed. Moreover, this criterion has been extended to characterize the stability of interval polynomials as well as fractional-order polynomials. Furthermore, it can help us to design stable and minimum-phase controllers. In this paper, theory and application of this criterion will be reviewed. Also, several illustrative examples are given.

Keywords: Hurwitz polynomials, Routh-Hurwitz stability criterion, continued fraction expansion, pure imaginary roots

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Authors: Michael Gidey Gebru

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Most DEA models operate in a static environment with input and output parameters that are chosen by deterministic data. However, due to ambiguity brought on shifting market conditions, input and output data are not always precisely gathered in real-world scenarios. Fuzzy numbers can be used to address this kind of ambiguity in input and output data. Therefore, this work aims to expand crisp DEA into DEA with fuzzy environment. In this study, the input and output data are regarded as fuzzy triangular numbers. Then, the DEA model with fuzzy environment is solved using a multi-objective method to gauge the Decision Making Units’ efficiency. Finally, the developed DEA model is illustrated with an application on real data 50 educational institutions.

Keywords: efficiency, DEA, fuzzy, decision making units, higher education institutions

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Authors: Denise Hexom, Judith Menoher

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Teachers and administrators across America are being asked to use data and hard evidence to inform practice as they begin the task of implementing Common Core State Standards. Yet, the courses they are taking in schools of education are not preparing teachers or principals to understand the data-driven decision making (DDDM) process nor to utilize data in a much more sophisticated fashion. DDDM has been around for quite some time, however, it has only recently become systematically and consistently applied in the field of education. This paper discusses the theoretical framework of DDDM; empirical evidence supporting the effectiveness of DDDM; a process a department in a school of education has utilized to implement DDDM; and recommendations to other schools of education who attempt to implement DDDM in their decision-making processes and in their students’ coursework.

Keywords: data-driven decision making, institute of higher education, special education, continuous improvement

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Authors: Yaeji Lim, Hee-Seok Oh

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The coherence analysis measures the linear time-invariant relationship between two data sets and has been studied various fields such as signal processing, engineering, and medical science. However classical coherence analysis tends to be sensitive to outliers and focuses only on mean relationship. In this paper, we generalized cross periodogram to quantile cross periodogram and provide richer inter-relationship between two data sets. This is a general version of Laplace cross periodogram. We prove its asymptotic distribution under the long range process and compare them with ordinary coherence through numerical examples. We also present real data example to confirm the usefulness of quantile coherence analysis.

Keywords: coherence, cross periodogram, spectrum, quantile

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Authors: Lazlo Fauth, Andreas Ligocki

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For cost-effective use of harvesters, expensive repairs and unplanned downtimes must be reduced as far as possible. The predictive detection of failing systems and the calculation of intelligent service intervals, necessary to avoid these factors, require in-depth knowledge of the machines' behavior. Such know-how needs permanent monitoring of the machine state from different technical perspectives. In this paper, three approaches will be presented as they are currently pursued in the publicly funded project PreForst at Ostfalia University of Applied Sciences. These include the intelligent linking of workshop and service data, sensors on the harvester, and a special online hydraulic oil condition monitoring system. Furthermore the paper shows potentials as well as challenges for the use of these data in the conception of a predictive maintenance system.

Keywords: predictive maintenance, condition monitoring, forest harvesting, forest engineering, oil data, hydraulic data

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Authors: Aidan N. Smallwood, Celestine R. Weegenaar, Jack N. Evans

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The intensive care unit (ICU) is a particularly resource heavy environment, in terms of staff, drugs and equipment required. Whilst many areas of the hospital are attempting to cut down on plastic use and minimise their impact on the environment, this has proven challenging within the confines of intensive care. Concurrently, as globalization has progressed over recent decades, there has been a tendency towards centralised manufacturing with international distribution networks for products, often covering large distances. In this study, we have modelled the standard consumption of plastic single-use items over the course of the first 24-hours of an average individual patient’s stay in a 12 bed ICU in the United Kingdom (UK). We have identified the country of manufacture and calculated the minimum possible distance travelled by each item from factory to patient. We have assumed direct transport via the shortest possible straight line from country of origin to the UK and have not accounted for transport within either country. Assuming an intubated patient with invasive haemodynamic monitoring and central venous access, there are a total of 52 distincts, largely plastic, disposable products which would reasonably be required in the first 24-hours after admission. Each product type has only been counted once to account for multiple items being shipped as one package. Travel distances from origin were summed to give the total distance combined for all 52 products. The minimum possible total distance travelled from country of origin to the UK for all types of product was 273,353 km, equivalent to 6.82 circumnavigations of the globe, or 71% of the way to the moon. The mean distance travelled was 5,256 km, approximately the distance from London to Mecca. With individual packaging for each item, the total weight of consumed products was 4.121 kg. The CO2 produced shipping these items by air freight would equate to 30.1 kg, however doing the same by sea would produce 0.2 kg CO2. Extrapolating these results to the 211,932 UK annual ICU admissions (2018-2019), even with the underestimates of distance and weight of our assumptions, air freight would account for 6586 tons CO2 emitted annually, approximately 130 times that of sea freight. Given the drive towards cost saving within the UK health service, and the decline of the local manufacturing industry, buying from intercontinental manufacturers is inevitable However, transporting all consumables by sea where feasible would be environmentally beneficial, as well as being less costly than air freight. At present, the NHS supply chain purchases from medical device companies, and there is no freely available information as to the transport mode used to deliver the product to the UK. This must be made available to purchasers in order to give a fuller picture of life cycle impact and allow for informed decision making in this regard.

Keywords: CO2, intensive care, plastic, transport

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Authors: H. Y. Jung, Ju H. Park, S. M. Lee

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A sampled-data controller is presented for solid oxide fuel cell systems which is expressed by a sector bounded nonlinear model. The sector bounded nonlinear systems, which have a feedback connection with a linear dynamical system and nonlinearity satisfying certain sector type constraints. Also, the sampled-data control scheme is very useful since it is possible to handle digital controller and increasing research efforts have been devoted to sampled-data control systems with the development of modern high-speed computers. The proposed control law is obtained by solving a convex problem satisfying several linear matrix inequalities. Simulation results are given to show the effectiveness of the proposed design method.

Keywords: sampled-data control, fuel cell, linear matrix inequalities, nonlinear control

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Authors: Yusuf Dawa Sidi, Abdulrahman Bulama Bizi

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The most dependable and precise source of climate data is often gauge observation. However, long-term records of gauge observations, on the other hand, are unavailable in many regions around the world. In recent years, a number of gridded climate datasets with high spatial and temporal resolutions have emerged as viable alternatives to gauge-based measurements. However, it is crucial to thoroughly evaluate their performance prior to utilising them in hydroclimatic applications. Therefore, this study aims to assess the effectiveness of NASA Prediction of Worldwide Energy Resources (NASA POWER) and Climate Research Unit (CRU) datasets in accurately estimating precipitation and temperature patterns within the dry region of Nigeria from 1990 to 2020. The study employs widely used statistical metrics and the Standardised Precipitation Index (SPI) to effectively capture the monthly variability of precipitation and temperature and inter-annual anomalies in rainfall. The findings suggest that CRU exhibited superior performance compared to NASA POWER in terms of monthly precipitation and minimum and maximum temperatures, demonstrating a high correlation and much lower error values for both RMSE and MAE. Nevertheless, NASA POWER has exhibited a moderate agreement with gauge observations in accurately replicating monthly precipitation. The analysis of the SPI reveals that the CRU product exhibits superior performance compared to NASA POWER in accurately reflecting inter-annual variations in rainfall anomalies. The findings of this study indicate that the CRU gridded product is often regarded as the most favourable gridded precipitation product.

Keywords: CRU, climate change, precipitation, SPI, temperature

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Authors: Hind Alshoubaki

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The world is now confronting a widespread urban phenomenon: refugee camps, which have mostly been established in ‘rushing mode,’ pointing toward affording temporary settlements for refugees that provide them with minimum levels of safety, security and protection from harsh weather conditions within a very short time period. In fact, those emergency settlements are transforming into permanent ones since time is a decisive factor in terms of construction and camps’ age. These play an essential role in transforming their temporary character into a permanent one that generates deep modifications to the city’s territorial structure, shaping a new identity and creating a contentious change in the city’s form and history. To achieve a better understanding for the transformation of refugee camps, this study is based on a mixed-methods approach: the qualitative approach explores different refugee camps and analyzes their transformation process in terms of population density and the changes to the city’s territorial structure and urban features. The quantitative approach employs a statistical regression analysis as a reliable prediction of refugees’ satisfaction within the Zaatari camp in order to predict its future transformation. Obviously, refugees’ perceptions of their current conditions will affect their satisfaction, which plays an essential role in transforming emergency settlements into permanent cities over time. The test basically discusses five main themes: the access and readiness of schools, the dispersion of clinics and shopping centers; the camp infrastructure, the construction materials, and the street networks. The statistical analysis showed that Syrian refugees were not satisfied with their current conditions inside the Zaatari refugee camp and that they had started implementing changes according to their needs, desires, and aspirations because they are conscious about the fact of their prolonged stay in this settlement. Also, the case study analyses showed that neglecting the fact that construction takes time leads settlements being created with below-minimum standards that are deteriorating and creating ‘slums,’ which lead to increased crime rates, suicide, drug use and diseases and deeply affect cities’ urban tissues. For this reason, recognizing the ‘temporary-eternal’ character of those settlements is the fundamental concept to consider refugee camps from the beginning as definite permanent cities. This is the key factor to minimize the trauma of displacement on both refugees and the hosting countries. Since providing emergency settlements within a short time period does not mean using temporary materials, having a provisional character or creating ‘makeshift cities.’

Keywords: refugee, refugee camp, temporary, Zaatari

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Authors: Daniel Benson, Yundan Gong, Hannah Kirk

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Advancement in national language processing techniques has led to increased data processing speeds, and reduced the need for cumbersome, manual data processing that is often required when processing data from multilateral organizations for specific purposes. As such, using named entity recognition (NER) modeling and the Organisation of Economically Developed Countries (OECD) Creditor Reporting System database, we present the first geotagged dataset of OECD donor Official Development Assistance (ODA) projects on a global, subnational basis. Our resulting data contains 52,086 ODA projects geocoded to subnational locations across 115 countries, worth a combined $87.9bn. This represents the first global, OECD donor ODA project database with geocoded projects. We use this new data to revisit old questions of how ‘well’ donors allocate ODA to the developing world. This understanding is imperative for policymakers seeking to improve ODA effectiveness.

Keywords: international aid, geocoding, subnational data, natural language processing, machine learning

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Authors: Guo Wenyu, Qu Youli

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A practical and simple self-indexing data structure, Partitioned Elias-Fano (PEF) - Compressed Suffix Arrays (CSA), is built in linear time for the CSA based on PEF indexes. Moreover, the PEF-CSA is compared with two classical compressed indexing methods, Ferragina and Manzini implementation (FMI) and Sad-CSA on different type and size files in Pizza & Chili. The PEF-CSA performs better on the existing data in terms of the compression ratio, count, and locates time except for the evenly distributed data such as proteins data. The observations of the experiments are that the distribution of the φ is more important than the alphabet size on the compression ratio. Unevenly distributed data φ makes better compression effect, and the larger the size of the hit counts, the longer the count and locate time.

Keywords: compressed suffix array, self-indexing, partitioned Elias-Fano, PEF-CSA

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Authors: Wanjiku Karanja

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Facebook has monopoly power in the social networking market. It has grown and entrenched its monopoly power through the capture of its users’ data value chains. However, antitrust law’s consumer welfare roots have prevented it from effectively addressing the role of data capture in Facebook’s market dominance. These regulatory blind spots are augmented in Facebook’s proposed Diem cryptocurrency project and its Novi Digital wallet. Novi, which is Diem’s digital identity component, shall enable Facebook to collect an unprecedented volume of consumer data. Consequently, Novi has seismic implications on internet identity as the network effects of Facebook’s large user base could establish it as the de facto internet identity layer. Moreover, the large tracts of data Facebook shall collect through Novi shall further entrench Facebook's market power. As such, the attendant lock-in effects of this project shall be very difficult to reverse. Urgent regulatory action is therefore required to prevent this expansion of Facebook’s data resources and monopoly power. This research thus highlights the importance of data capture to competition and market health in the social networking industry. It utilizes interviews with key experts to empirically interrogate the impact of Facebook’s data capture and control of its users’ data value chains on its market power. This inquiry is contextualized against Novi’s expansive effect on Facebook’s data value chains. It thus addresses the novel antitrust issues arising at the nexus of Facebook’s monopoly power and the privacy of its users’ data. It also explores the impact of platform design principles, specifically data portability and data portability, in mitigating Facebook’s anti-competitive practices. As such, this study finds that Facebook is a powerful monopoly that dominates the social media industry to the detriment of potential competitors. Facebook derives its power from its size, annexure of the consumer data value chain, and control of its users’ social graphs. Additionally, the platform design principles of data interoperability and data portability are not a panacea to restoring competition in the social networking market. Their success depends on the establishment of robust technical standards and regulatory frameworks.

Keywords: antitrust law, data protection law, data portability, data interoperability, digital identity, Facebook

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Authors: Camille Van Eupen, Dirk Maes, Marc Herremans, Kristijn R. R. Swinnen, Ben Somers, Stijn Luca

Abstract:

In ecology, species distribution models are commonly implemented to study species-environment relationships. These models increasingly rely on opportunistic citizen science data when high-quality species records collected through standardized recording protocols are unavailable. While these opportunistic data are abundant, uncertainty is usually high, e.g., due to observer effects or a lack of metadata. Data quality filtering is often used to reduce these types of uncertainty in an attempt to increase the value of studies relying on opportunistic data. However, filtering should not be performed blindly. In this study, recommendations are built for data quality filtering of opportunistic species occurrence data that are used as input for species distribution models. Using an extensive database of 5.7 million citizen science records from 255 species in Flanders, the impact on model performance was quantified by applying three data quality filters, and these results were linked to species traits. More specifically, presence records were filtered based on record attributes that provide information on the observation process or post-entry data validation, and changes in the area under the receiver operating characteristic (AUC), sensitivity, and specificity were analyzed using the Maxent algorithm with and without filtering. Controlling for sample size enabled us to study the combined impact of data quality filtering, i.e., the simultaneous impact of an increase in data quality and a decrease in sample size. Further, the variation among species in their response to data quality filtering was explored by clustering species based on four traits often related to data quality: commonness, popularity, difficulty, and body size. Findings show that model performance is affected by i) the quality of the filtered data, ii) the proportional reduction in sample size caused by filtering and the remaining absolute sample size, and iii) a species ‘quality profile’, resulting from a species classification based on the four traits related to data quality. The findings resulted in recommendations on when and how to filter volunteer generated and opportunistically collected data. This study confirms that correctly processed citizen science data can make a valuable contribution to ecological research and species conservation.

Keywords: citizen science, data quality filtering, species distribution models, trait profiles

Procedia PDF Downloads 203

Authors: Qi Xiu, Hiromu Hota, Yohsuke Ishii, Takuya Oda

Abstract:

Recently, collectable manufacturing data are rapidly increasing. On the other hand, mega recall is getting serious as a social problem. Under such circumstances, there are increasing needs for preventing mega recalls by defect analysis such as root cause analysis and abnormal detection utilizing manufacturing data. However, the time to classify strings in manufacturing data by traditional method is too long to meet requirement of quick defect analysis. Therefore, we present String Length Distribution Classification method (SLDC) to correctly classify strings in a short time. This method learns character features, especially string length distribution from Product ID, Machine ID in BOM and asset list. By applying the proposal to strings in actual manufacturing data, we verified that the classification time of strings can be reduced by 80%. As a result, it can be estimated that the requirement of quick defect analysis can be fulfilled.

Keywords: string classification, data quality, feature selection, probability distribution, string length

Procedia PDF Downloads 318

Authors: Okanlawon Simon Ayorinde, Odunjo Oluronke Omolola, Fadamiro Joseph Akinlabi, Adedibu Afolabi Adebgite

Abstract:

A road is a path established over land, especially prepared way between places for the use of pedestrian, riders, and vehicles: a hard surface built for vehicles to travel on. The social, economic and health importance of roads in any community and nation cannot be underestimated. Roads provide access to properties and they also provide mobility which is ability to transport goods and services from one place to another. In the residential zones of many indigenous cities in Nigeria, roads are usually blocked for social ceremonies. Road blocked for ceremonies as used in this study are a temporary barrier across a road, used to stop or hinder traffic from passing through to the other side. Social ceremonies that could warrant road blockage include marriage, child naming, funeral, celebration of life’s achievement, birthday anniversary etc. These activities are likely to generate environmental hazards and their attendant risks. The assessment of these hazards and risks in residential zones of indigenous cities in Nigeria becomes imperative. The study is focused on Ogbomoso, Oyo State, Nigeria. The town has two local government councils namely Ogbomoso North and Ogbomoso South. Urban tracts that are easy to identify are political wards in the absence of land use segregation, houses numbering and street naming. The wards that had residential having a minimum of 60% of their land use components were surveyed and fifteen out of twenty wards identified in the town were surveyed. The study utilized primary data collected through questionnaire administration The three major road categories (Trunk A-Federal; Trunk B- State; Trunk C-Local) were identified and trunk C-Local roads were purposively selected being the concern of this study because they are the ones often blocked for social activities. The major stakeholders interviewed and the respective sampling methods are residents (random and systematic), social ceremony organizers (purposive), government officials (purposive) and road users namely commercial motorists and commercial motor cyclists (random and incidental). Data analysis was mainly descriptive. Two indices to measure respondents’ perception were developed. These are ‘Hazard Severity Index’ (HSI) and ‘Relative Awareness Index’ (RAI).Thereafter, policy implications and recommendations were provided.

Keywords: road, residential zones, indigenous cities, blocked, social ceremonies

Procedia PDF Downloads 519