Search results for: magnetic observatory data

Authors: Jia Yi Yap, Angela S. H. Lee

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With the use of big data technologies, organization can get result that they are interested in. Big data technologies simply load all the data that is useful for the organizations and provide organizations a better way of analysing data. The purpose of this research is to get employees’ opinion from films in Malaysia to explore the use of big data technologies in their organization in order to provide how it may affect the perception of the employees on job performance. Therefore, in order to identify will accepting big data technologies in the organization affect the perception of the employee, questionnaire will be distributed to different employee from different Small and medium-sized enterprises (SME) organization listed in Malaysia. The conceptual model proposed will test with other variables in order to see the relationship between variables.

Keywords: big data technologies, employee, job performance, questionnaire

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Authors: Beulah Rani Inbanathan

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In the present era, it is vivid from the numerous outcomes that data privacy is being compromised in various ways. Machine learning is one technology that uses the centralized server, and then data is given as input which is being analyzed by the algorithms present on this mentioned server, and hence outputs are predicted. However, each time the data must be sent by the user as the algorithm will analyze the input data in order to predict the output, which is prone to threats. The solution to overcome this issue is federated learning, where the models alone get updated while the data resides on the local machine and does not get exchanged with the other local models. Nevertheless, even on these local models, there are chances of data poisoning, and it is crystal clear from various experiments done by many people. This paper delves into many ways where data poisoning occurs and the many methods through which it is prevalent that data poisoning still exists. It includes the poisoning attacks on IoT devices, Edge devices, Autoregressive model, and also, on Industrial IoT systems and also, few points on how these could be evadible in order to protect our data which is personal, or sensitive, or harmful when exposed.

Keywords: data poisoning, federated learning, Internet of Things, edge computing

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Authors: Mariza Kaskara, Stella Girtsou, Maria Prodromou, Alexia Tsouni, Christodoulos Mettas, Stavroula Alatza, Kyriaki Fotiou, Marios Tzouvaras, Charalampos Kontoes, Diofantos Hadjimitsis

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Natural hazard assessment and monitoring are crucial in managing the risks associated with fires, floods, and geohazards, particularly in regions prone to these natural disasters, such as Greece and Cyprus. Recent advancements in technology, developed by the BEYOND Center of Excellence of the National Observatory of Athens, have been successfully applied in Greece and are now set to be transferred to Cyprus. The implementation of these advanced technologies in Greece has significantly improved the country's ability to respond to these natural hazards. For wildfire risk assessment, a scalar wildfire occurrence risk index is created based on the predictions of machine learning models. Predicting fire danger is crucial for the sustainable management of forest fires as it provides essential information for designing effective prevention measures and facilitating response planning for potential fire incidents. A reliable forecast of fire danger is a key component of integrated forest fire management and is heavily influenced by various factors that affect fire ignition and spread. The fire risk model is validated by the sensitivity and specificity metric. For flood risk assessment, a multi-faceted approach is employed, including the application of remote sensing techniques, the collection and processing of data from the most recent population and building census, technical studies and field visits, as well as hydrological and hydraulic simulations. All input data are used to create precise flood hazard maps according to various flooding scenarios, detailed flood vulnerability and flood exposure maps, which will finally produce the flood risk map. Critical points are identified, and mitigation measures are proposed for the worst-case scenario, namely, refuge areas are defined, and escape routes are designed. Flood risk maps can assist in raising awareness and save lives. Validation is carried out through historical flood events using remote sensing data and records from the civil protection authorities. For geohazards monitoring (e.g., landslides, subsidence), Synthetic Aperture Radar (SAR) and optical satellite imagery are combined with geomorphological and meteorological data and other landslide/ground deformation contributing factors. To monitor critical infrastructures, including dams, advanced InSAR methodologies are used for identifying surface movements through time. Monitoring these hazards provides valuable information for understanding processes and could lead to early warning systems to protect people and infrastructure. Validation is carried out through both geotechnical expert evaluations and visual inspections. The success of these systems in Greece has paved the way for their transfer to Cyprus to enhance Cyprus's capabilities in natural hazard assessment and monitoring. This transfer is being made through capacity building activities, fostering continuous collaboration between Greek and Cypriot experts. Apart from the knowledge transfer, small demonstration actions are implemented to showcase the effectiveness of these technologies in real-world scenarios. In conclusion, the transfer of advanced natural hazard assessment technologies from Greece to Cyprus represents a significant step forward in enhancing the region's resilience to disasters. EXCELSIOR project funds knowledge exchange, demonstration actions and capacity-building activities and is committed to empower Cyprus with the tools and expertise to effectively manage and mitigate the risks associated with these natural hazards. Acknowledgement:Authors acknowledge the 'EXCELSIOR': ERATOSTHENES: Excellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment H2020 Widespread Teaming project.

Keywords: earth observation, monitoring, natural hazards, remote sensing

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Authors: Mohammad Al- Rawi, Ahmad Al- Jumaily

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This paper investigates the effect of developing arterial blockage at the abdominal aorta on the blood pressure waveform at an externally accessible location suitable for invasive measurements such as the brachial and the femoral arteries. Arterial blockages are created surgically within the abdominal aorta of healthy Wistar rats to create narrowing resemblance conditions. Blood pressure waveforms are measured using a catheter inserted into the right femoral artery. Measurements are taken at the baseline healthy condition as well as at four different severities (20%, 50%, 80% and 100%) of arterial blockage. In vivo and in vitro measurements of the lumen diameter and wall thickness are taken using Magnetic Resonance Imaging (MRI) and microscopic techniques, respectively. These data are used to validate a 3D computational fluid dynamics model (CFD) which is developed to generalize the outcomes of this work and to determine the arterial stress and strain under the blockage conditions. This work indicates that an arterial blockage in excess of 20% of the lumen diameter significantly influences the pulse wave and reduces the systolic blood pressure at the right femoral artery. High wall shear stress and low circumferential strain are also generated at the blockage site.

Keywords: arterial blockage, pulse wave, atherosclerosis, CFD

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Authors: T. Yılmaz, Ş. Tavman

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In this study, optimization of ultrasound assisted extraction (UAE) of hemicellulose based polysaccharides from plant waste material has been studied. Selected material is hazelnut skin. Extraction variables for the operation are extraction time, amplitude and application temperature. Optimum conditions have been evaluated depending on responses such as amount of wet crude polysaccharide, total carbohydrate content and dried sample. Pretreated hazelnut skin powders were used for the experiments. 10 grams of samples were suspended in 100 ml water in a jacketed vessel with additional magnetic stirring. Mixture was sonicated by immersing ultrasonic probe processor. After the extraction procedures, ethanol soluble and insoluble sides were separated for further examinations. The obtained experimental data were analyzed by analysis of variance (ANOVA). Second order polynomial models were developed using multiple regression analysis. The individual and interactive effects of applied variables were evaluated by Box Behnken Design. The models developed from the experimental design were predictive and good fit with the experimental data with high correlation coefficient value (R2 more than 0.95). Extracted polysaccharides from hazelnut skin are assumed to be pectic polysaccharides according to the literature survey of Fourier Transform Spectrometry (FTIR) analysis results. No more change can be observed between spectrums of different sonication times. Application of UAE at optimized condition has an important effect on extraction of hemicellulose from plant material by satisfying partial hydrolysis to break the bounds with other components in plant cell wall material. This effect can be summarized by varied intensity of microjets and microstreaming at varied sonication conditions.

Keywords: hazelnut skin, optimization, polysaccharide, ultrasound assisted extraction

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Authors: Bandari Shankar, Yohannes Yirga

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In this paper, the problem of heat and mass transfer in unsteady MHD boundary-layer flow of nanofluids over stretching sheet with a non uniform heat source/sink is considered. The unsteadiness in the flow and temperature is caused by the time-dependent stretching velocity and surface temperature. The unsteady boundary layer equations are transformed to a system of non-linear ordinary differential equations and solved numerically using Keller box method. The velocity, temperature, and concentration profiles were obtained and utilized to compute the skin-friction coefficient, local Nusselt number, and local Sherwood number for different values of the governing parameters viz. solid volume fraction parameter, unsteadiness parameter, magnetic field parameter, Schmidt number, space-dependent and temperature-dependent parameters for heat source/sink. A comparison of the numerical results of the present study with previously published data revealed an excellent agreement

Keywords: unsteady, heat and mass transfer, manetohydrodynamics, nanofluid, non-uniform heat source/sink, stretching sheet

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Authors: Rosemary Anibogwu, Kavita Sharma, Karl De Jesus

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Sagebrush is an abundant and naturally occurring plant in the Intermountain West region of the United States. The plant contains an array of bioactive compounds such as flavonoids, terpenoids, sterols, and phenolic acids. It is important to identify and characterize these compounds because Native Americans use sagebrush as herbal medicine. These compounds are also utilized for preventing infection in wounds, treating headaches and colds, and possess antitumor properties. This research is an exploratory study on the sesquiterpene present in the leaves of sagebrush. The leaf foliage was extracted with 100 % chloroform and 100 % methanol. The percentage yield for the crude was considerably higher in chloroform. The Thin Layer Chromatography (TLC) analysis of the crude extracted unveiled a brown band at Rf = 0.25 and a dark brown band at Rf = 0.74, along with three unknown faint bands the 254 nm UV lamp. Furthermore, the two distinct brown (Achillin) and dark brown band (Hydroxyachillin) in TLC were further utilized in the isolation of pure compounds with column chromatography. The structures of Achillin and Hydroxyachillin were elucidated based on extensive spectroscopic analysis, including TLC, High-Performance Liquid Chromatography (HPLC), 1D- and 2D-Nuclear Magnetic Resonance (NMR), and Mass Spectroscopy (MS). The antioxidant activities of crude extract and three pure compounds were evaluated in terms of their peroxyl radical scavenging by Ferric Reducing Ability of Plasma (FRAP) and 1,1-Diphenyl-2-picryl-hydrazyl (DPPH) methods. The crude extract showed the antioxidant activity of 18.99 ± 0.51 µmol TEg -1 FW for FRAP and 11.59 ± 0.38 µmol TEg -1 FW for DPPH. The activities of Achillin, Hydroxyachillin, and Quercetagetin trimethyl ether were 13.03, 15.90 and 14.02 µmol TEg -1 FW respectively for the FRAP assay. The three purified compounds have been submitted to the National Cancer Institute 60 cancer cell line for further study.

Keywords: HPLC, nuclear magnetic resonance spectroscopy, sagebrush, sesquiterpene lactones

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Authors: R. M. Kalayappan, N. Kathiravan

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In automobile industries, Controller Area Network (CAN) is widely used to reduce the system complexity and inter-task communication. Therefore, this paper proposes the hardware implementation of data frame communication between one controller to other. The CAN data frames and protocols will be explained deeply, here. The data frames are transferred without any collision or corruption. The simulation is made in the KEIL vision software to display the data transfer between transmitter and receiver in CAN. ARM7 micro-controller is used to transfer data’s between the controllers in real time. Data transfer is verified using the CRO.

Keywords: control area network (CAN), automotive electronic control unit, CAN 2.0, industry

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Authors: B. Bouadjemi, S. Bentata, W. Benstaali, A. Abbad

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The electronic and magnetic properties of the cubic praseodymium oxides perovskites PrMnO3 were calculated using the density functional theory (DFT) with both generalized gradient approximation (GGA) and GGA+U approaches, where U is on-site Coulomb interaction correction. The results show a half-metallic ferromagnetic ground state for PrMnO3 in GGA+U approached, while semi-metallic ferromagnetic character is observed in GGA. The results obtained, make the cubic PrMnO3 a promising candidate for application in spintronics.

Keywords: first-principles, electronic properties, transition metal, materials science

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Authors: Rajbir Cheema

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In order to introduce an integrated research information system, this will provide scientific institutions with the necessary information on research activities and research results in assured quality. Since data collection, duplication, missing values, incorrect formatting, inconsistencies, etc. can arise in the collection of research data in different research information systems, which can have a wide range of negative effects on data quality, the subject of data quality should be treated with better results. This paper examines the data quality problems in research information systems and presents the new techniques that enable organizations to improve their quality of research information.

Keywords: Research information systems (RIS), research information, heterogeneous sources, data quality, data cleansing, science system, standardization

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Authors: Carla Silva

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Recent development of information and communication technology enables us to acquire, collect, analyse data in various fields of socioeconomic – technological systems. Along with the increase of economic globalization and the evolution of information technology, data mining has become an important approach for economic data analysis. As a result, there has been a critical need for automated approaches to effective and efficient usage of massive amount of educational data, in order to support institutions to a strategic planning and investment decision-making. In this article, we will address data from several different perspectives and define the applied data to sciences. Many believe that 'big data' will transform business, government, and other aspects of the economy. We discuss how new data may impact educational policy and educational research. Large scale administrative data sets and proprietary private sector data can greatly improve the way we measure, track, and describe educational activity and educational impact. We also consider whether the big data predictive modeling tools that have emerged in statistics and computer science may prove useful in educational and furthermore in economics. Finally, we highlight a number of challenges and opportunities for future research.

Keywords: data mining, research analysis, investment decision-making, educational research

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Authors: P. Moskal, T. Bednarski, P. Bialas, E. Czerwinski, A. Gajos, A. Gruntowski, D. Kaminska, L. Kaplon, G. Korcyl, P. Kowalski, T. Kozik, W. Krzemien, E. Kubicz, Sz. Niedzwiecki, M. Palka, L. Raczynski, Z. Rudy, P. Salabura, N. G. Sharma, M. Silarski, A. Slomski, J. Smyrski, A. Strzelecki, A. Wieczorek, W. Wislicki, M. Zielinski, N. Zon

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A new concept and results of the performance tests of the TOF-PET detection system developed at the Jagiellonian University will be presented. The novelty of the concept lies in employing long strips of polymer scintillators instead of crystals as detectors of annihilation quanta, and in using predominantly the timing of signals instead of their amplitudes for the reconstruction of Lines-of-Response. The diagnostic chamber consists of plastic scintillator strips readout by pairs of photo multipliers arranged axially around a cylindrical surface. To take advantage of the superior timing properties of plastic scintillators the signals are probed in the voltage domain with the accuracy of 20 ps by a newly developed electronics, and the data are collected by the novel trigger-less and reconfigurable data acquisition system. The hit-position and hit-time are reconstructed by the dedicated reconstruction methods based on the compressing sensing theory and the library of synchronized model signals. The solutions are subject to twelve patent applications. So far a time-of-flight resolution of ~120 ps (sigma) was achieved for a double-strip prototype with 30 cm field-of-view (FOV). It is by more than a factor of two better than TOF resolution achievable in current TOF-PET modalities and at the same time the FOV of 30 cm long prototype is significantly larger with respect to typical commercial PET devices. The Jagiellonian PET (J-PET) detector with plastic scintillators arranged axially possesses also another advantage. Its diagnostic chamber is free of any electronic devices and magnetic materials thus giving unique possibilities of combining J-PET with CT and J-PET with MRI for scanning the same part of a patient at the same time with both methods.

Keywords: PET-CT, PET-MRI, TOF-PET, scintillator

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Authors: Karolina Siejka, Monika Piekarska, Monika Zbroja, Weronika Cyranka, Maryla Kuczynska, Magdalena Grzegorczyk, Malgorzata Nowakowska, Agnieszka Brodzisz, Magdalena Maria Wozniak

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Crohn’s disease is one of chronic inflammatory bowel diseases. It is increasing in prevalence worldwide, especially with young people. The disease usually occurs in the second to the fourth decade of life. Traditionally is diagnosed by clinical indicates, endoscopic, and histological findings. Magnetic Resonance Enterography (MRE) can demonstrate mural and extramural inflammatory signs and complications, which make it a valuable diagnostic modality. The study included 76 adults and 36 children diagnosed with Crohn’s disease. Each patient underwent MRE with intravenous administration of a contrast agent. All the studies were performed using Siemens Aera 1.5T scanner according to a local study protocol. Whenever applicable, MR Enterography findings were verified with endoscopy. Forty adults and all 36 children had an active phase of Crohn’s disease; five adults had a chronic phase of the disease; one adult had both chronic and active inflammatory features. Thirty adults have no sings of pathology. In both adult and pediatric groups the most commonly observed manifestation of active disease was thickened edematous ileum wall (26 adults and 36 children). Adults had Bauhin’s valve edema in 58% cases (n=23) and mesenteric changes in 34% cases (n=9). To compare, 32 children had Bauhin’s valve edema (89%) and, in 23 cases, was found inflammatory infiltration of the peri-intestinal fat (64%). The involvement of the large intestine was more common among children (100%). Complications of Crohn’s disease were found commonly in adults (40% of adults, 22% of children). There were observed 18 fistulas (14 adults, four children) and six abscesses (2 adults, four children). MRE is a reliable method in the evaluation of Crohn’s disease activity, especially of its complications. The lack of radiations makes MRE well-tolerated modality, which can be often repeated, particularly in young patients. The disease had different medical sings depending on age – children often had a more active inflammatory process, but there were more complications in the adult group.

Keywords: Crohn's disease, diagnostics, inflammatory bowel disease, magnetic resonance enterography, MRE

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Authors: Digvijaysingh S. Bana, Kiran R. Trivedi

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This paper introduces various methods for the alpha wave to detect the difference between two states of brain. One healthy subject participated in the experiment. EEG was measured on the forehead above the eye (FP1 Position) with reference and ground electrode are on the ear clip. The data samples are obtained in the form of EEG raw data. The time duration of reading is of one minute. Various test are being performed on the alpha band EEG raw data.The readings are performed in different time duration of the entire day. The statistical analysis is being carried out on the EEG sample data in the form of various tests.

Keywords: electroencephalogram(EEG), biometrics, authentication, EEG raw data

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Authors: Mohammadreza Hedyehzadeh, Mahdi Yousefi

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Colon cancer is one of the most common cancer, which predicted to increase its prevalence due to the bad eating habits of peoples. Nowadays, due to the busyness of people, the use of fast foods is increasing, and therefore, diagnosis of this disease and its treatment are of particular importance. To determine the best treatment approach for each specific colon cancer patients, the oncologist should be known the stage of the tumor. The most common method to determine the tumor stage is TNM staging system. In this system, M indicates the presence of metastasis, N indicates the extent of spread to the lymph nodes, and T indicates the size of the tumor. It is clear that in order to determine all three of these parameters, an imaging method must be used, and the gold standard imaging protocols for this purpose are CT and PET/CT. In CT imaging, due to the use of X-rays, the risk of cancer and the absorbed dose of the patient is high, while in the PET/CT method, there is a lack of access to the device due to its high cost. Therefore, in this study, we aimed to estimate the tumor size and the extent of its spread to the lymph nodes using MR images. More than 1300 MR images collected from the TCIA portal, and in the first step (pre-processing), histogram equalization to improve image qualities and resizing to get the same image size was done. Two expert radiologists, which work more than 21 years on colon cancer cases, segmented the images and extracted the tumor region from the images. The next step is feature extraction from segmented images and then classify the data into three classes: T0N0، T3N1 و T3N2. In this article, the VGG-16 convolutional neural network has been used to perform both of the above-mentioned tasks, i.e., feature extraction and classification. This network has 13 convolution layers for feature extraction and three fully connected layers with the softmax activation function for classification. In order to validate the proposed method, the 10-fold cross validation method used in such a way that the data was randomly divided into three parts: training (70% of data), validation (10% of data) and the rest for testing. It is repeated 10 times, each time, the accuracy, sensitivity and specificity of the model are calculated and the average of ten repetitions is reported as the result. The accuracy, specificity and sensitivity of the proposed method for testing dataset was 89/09%, 95/8% and 96/4%. Compared to previous studies, using a safe imaging technique (MRI) and non-use of predefined hand-crafted imaging features to determine the stage of colon cancer patients are some of the study advantages.

Keywords: colon cancer, VGG-16, magnetic resonance imaging, tumor size, lymph node metastasis

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Authors: L. Tonia, I. Daglis, W. Kurth

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The sound of the universe creates an affinity with the sounds of music. The analysis of the sound of space focuses on the existence of a tone material, the microstructure and macrostructure, and the form of the sound through the signals recorded during the flight of the spacecraft Van Allen Probes and Cassini’s mission. The sound becomes from the frequencies that belong to electromagnetic waves. Plasma Wave Science Instrument and Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) recorded the signals from space. A transformation of that signals to audio gave the opportunity to study and analyze the sound. Due to the fact that the musical tone pitch has a frequency and every electromagnetic wave produces a frequency too, the creation of a musical score, which appears as the sound of space, can give information about the form, the symmetry, and the harmony of the sound. The conversion of space radio emissions to audio provides a number of tone pitches corresponding to the original frequencies. Through the process of these sounds, we have the opportunity to present a music score that “composed” from space. In this score, we can see some basic features associated with the music form, the structure, the tone center of music material, the construction and deconstruction of the sound. The structure, which was built through a harmonic world, includes tone centers, major and minor scales, sequences of chords, and types of cadences. The form of the sound represents the symmetry of a spiral movement not only in micro-structural but also to macro-structural shape. Multiple glissando sounds in linear and polyphonic process of the sound, founded in magnetic fields around Earth, Saturn, and Jupiter, but also a spiral movement appeared on the spectrogram of the sound. Whistles, Auroral Kilometric Radiations, and Chorus emissions reveal movements similar to musical excerpts of works by contemporary composers like Sofia Gubaidulina, Iannis Xenakis, EinojuhamiRautavara.

Keywords: space sound analysis, spiral, space music, analysis

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Authors: Chhavi Rana

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The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, Healthcare, and business intelligence contain voluminous and incremental data, which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organization's decision-making strategy can be enhanced using big data analytics and applying different machine learning techniques and statistical tools on such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates on various frameworks in the process of Analysis using different machine-learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

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Authors: Chhavi Rana

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The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, healthcare, and business intelligence contain voluminous and incremental data which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organisation decision-making strategy can be enhanced by using big data analytics and applying different machine learning techniques and statistical tools to such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates various frameworks in the process of analysis using different machine learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

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Authors: Ji Eun Shin, Dong Hoon Lim

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Data clustering is a common technique used in data analysis and is used in many applications, such as artificial intelligence, pattern recognition, economics, ecology, psychiatry and marketing. K-means clustering is a well-known clustering algorithm aiming to cluster a set of data points to a predefined number of clusters. In this paper, we implement K-means algorithm based on MapReduce framework with RHadoop to make the clustering method applicable to large scale data. RHadoop is a collection of R packages that allow users to manage and analyze data with Hadoop. The main idea is to introduce a combiner as a function of our map output to decrease the amount of data needed to be processed by reducers. The experimental results demonstrated that K-means algorithm using RHadoop can scale well and efficiently process large data sets on commodity hardware. We also showed that our K-means algorithm using RHadoop with combiner was faster than regular algorithm without combiner as the size of data set increases.

Keywords: big data, combiner, K-means clustering, RHadoop

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Authors: Lucia Liu, Matthew Koziol

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Obsessive-compulsive disorder (OCD), a long-lasting anxiety disorder involving recurrent, intrusive thoughts, affects over 2 million adults in the United States. Transcranial magnetic stimulation (TMS) stands out as a noninvasive, cutting-edge therapy that has been shown to reduce symptoms in patients with treatment-resistant OCD. The Food and Drug Administration (FDA) approved protocol pairs TMS sessions with individualized symptom provocation, aiming to improve the susceptibility of brain circuits to stimulation. However, limited standardization or guidance exists on how to conduct symptom provocation and which methods are most effective. This study aims to compare the effect of internal versus external techniques to induce obsessional stress in a clinical setting during TMS therapy. Two symptom provocation methods, (i) Asking patients thought-provoking questions about their obsessions (internal) and (ii) Requesting patients to perform obsession-related tasks (external), were employed in a crossover design with repeated measurement. Thirty-six treatments of NeuroStar TMS were administered to each of two patients over 8 weeks in an outpatient clinic. Patient One received 18 sessions of internal provocation followed by 18 sessions of external provocation, while Patient Two received 18 sessions of external provocation followed by 18 sessions of internal provocation. The primary outcome was the level of self-reported obsessional stress on a visual analog scale from 1 to 10. The secondary outcome was self-reported OCD severity, collected biweekly in a four-level Likert-scale (1 to 4) of bad, fair, good and excellent. Outcomes were compared and tested between provocation arms through repeated measures ANOVA, accounting for intra-patient correlations. Ages were 42 for Patient One (male, White) and 57 for Patient Two (male, White). Both patients had similar moderate symptoms at baseline, as determined through the Yale-Brown Obsessive Compulsive Scale (YBOCS). When comparing obsessional stress induced across the two arms of internal and external provocation methods, the mean (SD) was 6.03 (1.18) for internal and 4.01 (1.28) for external strategies (P=0.0019); ranges were 3 to 8 for internal and 2 to 8 for external strategies. Internal provocation yielded 5 (31.25%) bad, 6 (33.33%) fair, 3 (18.75%) good, and 2 (12.5%) excellent responses for OCD status, while external provocation yielded 5 (31.25%) bad, 9 (56.25%) fair, 1 (6.25%) good, and 1 (6.25%) excellent responses (P=0.58). Internal symptom provocation tactics had a significantly stronger impact on inducing obsessional stress and led to better OCD status (non-significant). This could be attributed to the fact that answering questions may prompt patients to reflect more on their lived experiences and struggles with OCD. In the future, clinical trials with larger sample sizes are warranted to validate this finding. Results support the increased integration of internal methods into structured provocation protocols, potentially reducing the time required for provocation and achieving greater treatment response to TMS.

Keywords: obsessive-compulsive disorder, transcranial magnetic stimulation, mental health, symptom provocation

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Authors: Nikita Valluri, Vatcharaporn Esichaikul

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With the popularity of data-driven decision making on the rise, this study focuses on providing an alternative outlook towards the process of decision-making. Combining quantitative and qualitative methods rooted in the social sciences, an integrated framework is presented with a focus on delivering a much more robust and efficient approach towards the concept of data-driven decision-making with respect to not only Big data but also 'Thick data', a new form of qualitative data. In support of this, an example from the retail sector has been illustrated where the framework is put into action to yield insights and leverage business intelligence. An interpretive approach to analyze findings from both kinds of quantitative and qualitative data has been used to glean insights. Using traditional Point-of-sale data as well as an understanding of customer psychographics and preferences, techniques of data mining along with qualitative methods (such as grounded theory, ethnomethodology, etc.) are applied. This study’s final goal is to establish the framework as a basis for providing a holistic solution encompassing both the Big and Thick aspects of any business need. The proposed framework is a modified enhancement in lieu of traditional data-driven decision-making approach, which is mainly dependent on quantitative data for decision-making.

Keywords: big data, customer behavior, customer experience, data mining, qualitative methods, quantitative methods, thick data

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Authors: Takahiro Nishigaki, Katsumi Nitta, Takashi Onoda

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In this paper, we present a method of applying Independent Topic Analysis (ITA) to increasing the number of document data. The number of document data has been increasing since the spread of the Internet. ITA was presented as one method to analyze the document data. ITA is a method for extracting the independent topics from the document data by using the Independent Component Analysis (ICA). ICA is a technique in the signal processing; however, it is difficult to apply the ITA to increasing number of document data. Because ITA must use the all document data so temporal and spatial cost is very high. Therefore, we present Incremental ITA which extracts the independent topics from increasing number of document data. Incremental ITA is a method of updating the independent topics when the document data is added after extracted the independent topics from a just previous the data. In addition, Incremental ITA updates the independent topics when the document data is added. And we show the result applied Incremental ITA to benchmark datasets.

Keywords: text mining, topic extraction, independent, incremental, independent component analysis

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Authors: Sami Kabir, Sadek Hossain Khoka

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Open Government Data (OGD) refers to all data produced by government which are accessible in reusable way by common people with access to Internet and at free of cost. In line with “Digital Bangladesh” vision of Bangladesh government, the concept of open data has been gaining momentum in the country. Opening all government data in digital and customizable format from single platform can enhance e-governance which will make government more transparent to the people. This paper presents a well-in-progress case study on OGD portal by Bangladesh Government in order to link decentralized data. The initiative is intended to facilitate e-service towards citizens through this one-stop web portal. The paper further discusses ways of collecting data in digital format from relevant agencies with a view to making it publicly available through this single point of access. Further, possible layout of this web portal is presented.

Keywords: e-governance, one-stop web portal, open government data, reusable data, web of data

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Authors: Ahmad Lutfi, Nikolas Dhega

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The Malala deposit in northwest Sulawesi is the only known porphyry molybdenum and the only source for rhenium, occurrence in Indonesia. The neural network method produces results that correspond very closely to those of the knowledge-based fuzzy logic method and weights of evidence method. This method required data of solid geology, regional faults, airborne magnetic, gamma-ray survey data and GIS data. This interpretation of the network output fits with the intuitive notion that a prospective area has characteristics that closely resemble areas known to contain mineral deposits. Contrasts with the weights of evidence and fuzzy logic methods, where, for a given grid location, each input-parameter value automatically results in an increase in the prospective estimated. Malala District indicated molybdenum anomalies in stream sediments from in excess of 15 km2 were obtained, including the Takudan Fault as most prominent structure with striking 40̊ to 60̊ over a distance of about 30 km and in most places weakly at anomaly B, developed over an area of 4 km2, with a ‘shell’ up to 50 m thick at the intrusive contact with minor mineralization occurring in the Tinombo Formation. Series of NW trending, steeply dipping fracture zones, named the East Zone has an estimated resource of 100 Mt at 0.14% MoS2 and minimum target of 150 Mt 0.25%. The Malala porphyries occur as stocks and dykes with predominantly granitic, with fluorine-poor class of molybdenum deposits and belongs to the plutonic sub-type. Unidirectional solidification textures consisting of subparallel, crenulated layers of quartz that area separated by layers of intrusive material textures. The deuteric nature of the molybdenum mineralization and the dominance of carbonate alteration.The nature of the Stage I with alteration barren quartz K‐feldspar; and Stage II with alteration quartz‐K‐feldspar‐apatite-molybdenite veins combined with the presence of disseminated molybdenite with primary biotite in the host intrusive.

Keywords: molybdenite, Malala, porphyries, anomaly B

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Authors: Gabriela Wyszogrodzka, Przemyslaw Dorozynski, Barbara Gil, Maciej Strzempek, Bartosz Marszalek, Piotr Kulinowski, Wladyslaw Piotr Weglarz, Elzbieta Menaszek

Abstract:

MOFs (Metal-Organic Frameworks) belong to a new group of porous materials with a hybrid organic-inorganic construction. Their structure is a network consisting of metal cations or clusters (acting as metallic centers, nodes) and the organic linkers between nodes. The interest in MOFs is primarily associated with the use of their well-developed surface and large porous. Possibility to build MOFs of biocompatible components let to use them as potential drug carriers. Furthermore, forming MOFs structure from cations possessing paramagnetic properties (e.g. iron cations) allows to use them as MRI (Magnetic Resonance Imaging) contrast agents. The concept of formation of particles that combine the ability to transfer active substance with imaging properties has been called theranostic (from words combination therapy and diagnostics). By building MOF structure from iron cations it is possible to use them as theranostic agents and monitoring the distribution of the active substance after administration in real time. In the study iron-MOF: Fe-MIL-101-NH2 was chosen, consisting of iron cluster in nodes of the structure and amino-terephthalic acid as a linker. The aim of the study was to investigate the possibility of applying Fe-MIL-101-NH2 as inhalable theranostic particulate system for the first-line anti-tuberculosis antibiotic – isoniazid. The drug content incorporated into Fe-MIL-101-NH2 was evaluated by dissolution study using spectrophotometric method. Results showed isoniazid encapsulation efficiency – ca. 12.5% wt. Possibility of Fe-MIL-101-NH2 application as the MRI contrast agent was demonstrated by magnetic resonance tomography. FeMIL-101-NH2 effectively shortening T1 and T2 relaxation times (increasing R1 and R2 relaxation rates) linearly with the concentrations of suspended material. Images obtained using multi-echo magnetic resonance imaging sequence revealed possibility to use FeMIL-101-NH2 as positive and negative contrasts depending on applied repetition time. MOFs micronization via ultrasound was evaluated by XRD, nitrogen adsorption, FTIR, SEM imaging and did not influence their crystal shape and size. Ultrasonication let to break the aggregates and achieve very homogeneously looking SEM images. MOFs cytotoxicity was evaluated in in vitro test with a highly sensitive resazurin based reagent PrestoBlue™ on L929 fibroblast cell line. After 24h no inhibition of cell proliferation was observed. All results proved potential possibility of application of ironMOFs as an isoniazid carrier and as MRI contrast agent in inhalatory treatment of tuberculosis. Acknowledgments: Authors gratefully acknowledge the National Science Center Poland for providing financial support, grant no 2014/15/B/ST5/04498.

Keywords: imaging agents, metal-organic frameworks, theranostics, tuberculosis

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Authors: Soledad Carinelli, Iñigo Fernández, José Luis González-Mora, Pedro A. Salazar-Carballo

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Mastitis is the most relevant inflammatory disease in cattle, affecting the animal health and causing important economic losses on dairy farms. This disease takes place in the mammary gland or udder when some opportunistic microorganisms, such as Staphylococcus aureus, Streptococcus agalactiae, Corynebacterium bovis, etc., invade the teat canal. According to the severity of the inflammation, mastitis can be classified as sub-clinical, clinical and chronic. Standard methods for mastitis detection include counts of somatic cells, cell culture, electrical conductivity of the milk, and California test (evaluation of “gel-like” matrix consistency after cell lysed with detergents). However, these assays present some limitations for accurate detection of subclinical mastitis. Currently, haptoglobin, an acute phase protein, has been proposed as novel and effective biomarker for mastitis detection. In this work, an electrochemical biosensor based on polydopamine-modified magnetic nanoparticles (MNPs@pDA) for haptoglobin detection is reported. Thus, MNPs@pDA has been synthesized by our group and functionalized with hemoglobin due to its high affinity to haptoglobin protein. The protein was labeled with specific antibodies modified with alkaline phosphatase enzyme for its electrochemical detection using an electroactive substrate (1-naphthyl phosphate) by differential pulse voltammetry. After the optimization of assay parameters, the haptoglobin determination was evaluated in milk. The strategy presented in this work shows a wide range of detection, achieving a limit of detection of 43 ng/mL. The accuracy of the strategy was determined by recovery assays, being of 84 and 94.5% for two Hp levels around the cut off value. Milk real samples were tested and the prediction capacity of the electrochemical biosensor was compared with a Haptoglobin commercial ELISA kit. The performance of the assay has demonstrated this strategy is an excellent and real alternative as screen method for sub-clinical bovine mastitis detection.

Keywords: bovine mastitis, haptoglobin, electrochemistry, magnetic nanoparticles, polydopamine

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Authors: Elizaveta S. Prokofyeva, Svetlana V. Maltseva, Roman D. Zaitsev

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Rapidly evolving modern data analysis technologies in healthcare play a large role in understanding the operation of the system and its characteristics. Nowadays, one of the key tasks in urban healthcare is to optimize the resource allocation. Thus, the application of data analysis in medical institutions to solve optimization problems determines the significance of this study. The purpose of this research was to establish the dependence between the indicators of the effectiveness of the medical institution and its resources. Hospital discharges by diagnosis; hospital days of in-patients and in-patient average length of stay were selected as the performance indicators and the demand of the medical facility. The hospital beds by type of care, medical technology (magnetic resonance tomography, gamma cameras, angiographic complexes and lithotripters) and physicians characterized the resource provision of medical institutions for the developed models. The data source for the research was an open database of the statistical service Eurostat. The choice of the source is due to the fact that the databases contain complete and open information necessary for research tasks in the field of public health. In addition, the statistical database has a user-friendly interface that allows you to quickly build analytical reports. The study provides information on 28 European for the period from 2007 to 2016. For all countries included in the study, with the most accurate and complete data for the period under review, predictive models were developed based on historical panel data. An attempt to improve the quality and the interpretation of the models was made by cluster analysis of the investigated set of countries. The main idea was to assess the similarity of the joint behavior of the variables throughout the time period under consideration to identify groups of similar countries and to construct the separate regression models for them. Therefore, the original time series were used as the objects of clustering. The hierarchical agglomerate algorithm k-medoids was used. The sampled objects were used as the centers of the clusters obtained, since determining the centroid when working with time series involves additional difficulties. The number of clusters used the silhouette coefficient. After the cluster analysis it was possible to significantly improve the predictive power of the models: for example, in the one of the clusters, MAPE error was only 0,82%, which makes it possible to conclude that this forecast is highly reliable in the short term. The obtained predicted values of the developed models have a relatively low level of error and can be used to make decisions on the resource provision of the hospital by medical personnel. The research displays the strong dependencies between the demand for the medical services and the modern medical equipment variable, which highlights the importance of the technological component for the successful development of the medical facility. Currently, data analysis has a huge potential, which allows to significantly improving health services. Medical institutions that are the first to introduce these technologies will certainly have a competitive advantage.

Keywords: data analysis, demand modeling, healthcare, medical facilities

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Authors: C. B. Abhilash, Kavi Mahesh

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Human beings are the most advanced species on earth; it's all because of the ability to communicate and share information via human language. In today's world, a huge amount of data is available on the web in text format. This has also resulted in the generation of big data in structured and unstructured formats. In general, the data is in the textual form, which is highly unstructured. To get insights and actionable content from this data, we need to incorporate the concepts of text mining and natural language processing. In our study, we mainly focus on Interesting data through which interesting facts are generated for the knowledge base. The approach is to derive the analytics from the text via the application of natural language processing. Using semantic web Resource framework descriptors (RDF), we generate the triple from the given data and derive the interesting patterns. The methodology also illustrates data integration using the RDF for reliable, interesting patterns.

Keywords: RDF, interestingness, knowledge base, semantic data

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Authors: Nader Nciri, Suil Song, Namho Kim, Namjun Cho

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Properties and compositions of bitumen and bitumen-derived liquids have significant influences on the selection of recovery, upgrading and refining processes. Optimal process conditions can often be directly related to these properties. The end uses of bitumen and bitumen products are thus related to their compositions. Because it is not possible to conduct a complete analysis of the molecular structure of bitumen, characterization must be made in other terms. The present paper focuses on physico-chemical analysis of two different types of bitumens. These bitumen samples were chosen based on: the original crude oil (sand oil and crude petroleum), and mode of process. The aim of this study is to determine both the manufacturing effect on chemical species and the chemical organization as a function of the type of bitumen sample. In order to obtain information on bitumen chemistry, elemental analysis (C, H, N, S, and O), heavy metal (Ni, V) concentrations, IATROSCAN chromatography (thin layer chromatography-flame ionization detection), FTIR spectroscopy, and 1H NMR spectroscopy have all been used. The characterization includes information about the major compound types (saturates, aromatics, resins and asphaltenes) which can be compared with similar data for other bitumens, more importantly, can be correlated with data from petroleum samples for which refining characteristics are known. Examination of Asphalt Ridge froth bitumen showed that it differed significantly from representative petroleum pitches, principally in their nonhydrocarbon content, heavy metal content and aromatic compounds. When possible, properties and composition were related to recovery and refining processes. This information is important because of the effects that composition has on recovery and processing reactions.

Keywords: froth bitumen, oil sand, asphalt ridge, petroleum pitch, thin layer chromatography-flame ionization detection, infrared spectroscopy, 1H nuclear magnetic resonance spectroscopy

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Authors: Dina Ahmad Alkhodary

Abstract:

This study aimed to investigate the practices of Data Mining on the telecommunication companies in Jordan, from the viewpoint of the respondents. In order to achieve the goal of the study, and test the validity of hypotheses, the researcher has designed a questionnaire to collect data from managers and staff members from main department in the researched companies. The results shows improvements stages of the telecommunications companies towered Data Mining.

Keywords: data, mining, development, business

Procedia PDF Downloads 485