Search results for: data mining techniques

Authors: Marcho Setiawan Handok, Samuel S. Lemma, Abdoulaye Fofana, Naseef Mansoor

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This paper is proposing a method to predict the outcome of the National Football League match with data from 2019 to 2022 and compare it with other popular models. The model uses open-source statistical data of each team, such as passing yards, rushing yards, fumbles lost, and scoring. Each statistical data has offensive and defensive. For instance, a data set of anticipated values for a specific matchup is created by comparing the offensive passing yards obtained by one team to the defensive passing yards given by the opposition. We evaluated the model’s performance by contrasting its result with those of established prediction algorithms. This research is using a neural network to predict the score of a National Football League match and then predict the winner of the game.

Keywords: game prediction, NFL, football, artificial neural network

Procedia PDF Downloads 78

Authors: Khalid M. Kheiralla, Georgios Boutsis, Mohammed Y. Abdelgalil, Mohammed A. Ali, Nuha E. Mohamed

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The present study focus on integrated geoelectrical surveys carried out in the mineralization zone in Erkowit region, Eastern Sudan to determine the extensions of the potential ore deposits on the topographically high hilly area and under the cover of alluvium along the nearby wadi and to locate other occurrences if any. The magnetic method (MAG) and the electrical resistivity tomography (ERT) were employed for the survey. Eleven traverses were aligned approximately at right angles to the general strike of the rock formations. The disseminated sulfides are located on the alteration shear zone which is composed of granitic and dioritic highly ferruginated rock occupying the southwestern and central parts of the area, this was confirmed using thin and polished sections mineralogical analysis. The magnetic data indicates low magnetic values for wadi sedimentary deposits in its southern part of the area, and high anomalies which are suspected as gossans due to magnetite formed during wall rock alteration consequent to mineralization. The significant ERT images define low resistivity zone as traced as sheared zones which may associated with the main loci of ore deposition. By itself, no geophysical anomaly can simply be correlated with lithology, instead, magnetic and ERT anomalies raised due to variations in some specific physical properties of rocks which were extremely useful in mineral exploration.

Keywords: ERT, magnetic, mineralization, Red Sea, Sudan

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Authors: Dyana Zainudin, Atta Ur-Rahman, Thaier Hamed

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This paper explains about human nature concept as to understand the significance of information security in employees’ mentality including leaders in an organisation. By studying on a theory concept of the latest Von Solms fourth waves, information security governance basically refers to the concept of a set of methods, techniques and tools that responsible for protecting resources of a computer system to ensure service availability, confidentiality and integrity of information. However, today’s information security dilemma relates to the acceptance of employees mentality. The major causes are a lack of communication and commitment. These types of management in an organisation are labelled as immoral/amoral management which effects on information security compliance. A recovery action is taken based on ‘learn a lesson from incident events’ rather than prevention. Therefore, the paper critically analysed the Von Solms fourth waves’ theory with current human events and its correlation by studying secondary data and also from qualitative analysis among employees in public sectors. ‘Three-dimensions to failure’ of information security dilemma are explained as deny, don’t know and don’t care. These three-dimensions are the most common vulnerable behaviour owned by employees. Therefore, by avoiding the three-dimensions to failure may improve the vulnerable behaviour of employees which is often related to immoral/amoral management.

Keywords: information security management system, information security behaviour, information security governance, information security culture

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Authors: Mehdi Khaki, Ehsan Forootan, Joseph Awange, Michael Kuhn

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Terrestrial water storage, as a source of freshwater, plays an important role in human lives. Hydrological models offer important tools for simulating and predicting water storages at global and regional scales. However, their comparisons with 'reality' are imperfect mainly due to a high level of uncertainty in input data and limitations in accounting for all complex water cycle processes, uncertainties of (unknown) empirical model parameters, as well as the absence of high resolution (both spatially and temporally) data. Data assimilation can mitigate this drawback by incorporating new sets of observations into models. In this effort, we use multi-mission satellite-derived remotely sensed observations to improve the performance of World-Wide Water Resources Assessment system (W3RA) hydrological model for estimating terrestrial water storages. For this purpose, we assimilate total water storage (TWS) data from the Gravity Recovery And Climate Experiment (GRACE) and surface soil moisture data from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) into W3RA. This is done to (i) improve model estimations of water stored in ground and soil moisture, and (ii) assess the impacts of each satellite of data (from GRACE and AMSR-E) and their combination on the final terrestrial water storage estimations. These data are assimilated into W3RA using the Ensemble Square-Root Filter (EnSRF) filtering technique over Mississippi Basin (the United States) and Murray-Darling Basin (Australia) between 2002 and 2013. In order to evaluate the results, independent ground-based groundwater and soil moisture measurements within each basin are used.

Keywords: data assimilation, GRACE, AMSR-E, hydrological model, EnSRF

Procedia PDF Downloads 280

Authors: Kayla Renteria

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This study explored the role animal-assisted psychotherapy (AAP) can play in treating Post-Traumatic Stress Disorder (PTSD) when incorporated into Trauma-informed cognitive behavioral therapy (TF-CBT). A review of the literature was performed to show how incorporating AAP could benefit TF-CBT since this treatment model often presents difficulties, such as client motivation and avoidance of the exposure element of the intervention. In addition, the fluidity of treatment goals during complex trauma cases was explored, as this issue arose in the case study. This study follows the course of treatment of a 12-year-old female presenting with symptoms of PTSD. Treatment consisted of traditional components of the TF-CBT model, with the added elements of AAP to address typical treatment obstacles in TF-CBT. A registered therapy dog worked with the subject in all sessions throughout her treatment. The therapy dog was incorporated into components such as relaxation and coping techniques, narrative therapy techniques, and psychoeducation on the cognitive triangle. Throughout the study, the client’s situation and clinical needs required the therapist to switch goals to focus on current safety and stability. The therapy dog provided support and neurophysiological benefits to the client through AAP during this shift in treatment. The client was assessed quantitatively using the Child PTSD Symptom Scale Self Report for DSM-5 (CPSS-SR-5) before and after therapy and qualitatively through a feedback form given after treatment. The participant showed improvement in CPSS-SR-V scores, and she reported that the incorporation of the therapy animal improved her therapy. The results of this study show how the use of AAP provided the client a solid, consistent relationship with the therapy dog that supported her through processing various types of traumas. Implications of the results of treatment and for future research are discussed.

Keywords: animal-assisted therapy, trauma-focused cognitive behavioral therapy, PTSD in children, trauma treatment

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Authors: Gerhard Gritsch, Ana Skupch, Manfred Hartmann, Wolfgang Frühwirt, Hannes Perko, Dieter Grossegger, Tilmann Kluge

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Rehabilitation of stroke patients is dominated by classical physiotherapy. Nowadays, a field of research is the application of neurofeedback techniques in order to help stroke patients to get rid of their motor impairments. Especially, if a certain limb is completely paralyzed, neurofeedback is often the last option to cure the patient. Certain exercises, like the imagination of the impaired motor function, have to be performed to stimulate the neuroplasticity of the brain, such that in the neighboring parts of the injured cortex the corresponding activity takes place. During the exercises, it is very important to keep the motivation of the patient at a high level. For this reason, the missing natural feedback due to a movement of the effected limb may be replaced by a synthetic feedback based on the motor-related brain function. To generate such a synthetic feedback a system is needed which measures, detects, localizes and visualizes the motor related µ-rhythm. Fast therapeutic success can only be achieved if the feedback features high specificity, comes in real-time and without large delay. We describe such an approach that offers a 3D visualization of µ-rhythms in real time with a delay of 500ms. This is accomplished by combining smart EEG preprocessing in the frequency domain with source localization techniques. The algorithm first selects the EEG channel featuring the most prominent rhythm in the alpha frequency band from a so-called motor channel set (C4, CZ, C3; CP6, CP4, CP2, CP1, CP3, CP5). If the amplitude in the alpha frequency band of this certain electrode exceeds a threshold, a µ-rhythm is detected. To prevent detection of a mixture of posterior alpha activity and µ-activity, the amplitudes in the alpha band outside the motor channel set are not allowed to be in the same range as the main channel. The EEG signal of the main channel is used as template for calculating the spatial distribution of the µ - rhythm over all electrodes. This spatial distribution is the input for a inverse method which provides the 3D distribution of the µ - activity within the brain which is visualized in 3D as color coded activity map. This approach mitigates the influence of lid artifacts on the localization performance. The first results of several healthy subjects show that the system is capable of detecting and localizing the rarely appearing µ-rhythm. In most cases the results match with findings from visual EEG analysis. Frequent eye-lid artifacts have no influence on the system performance. Furthermore, the system will be able to run in real-time. Due to the design of the frequency transformation the processing delay is 500ms. First results are promising and we plan to extend the test data set to further evaluate the performance of the system. The relevance of the system with respect to the therapy of stroke patients has to be shown in studies with real patients after CE certification of the system. This work was performed within the project ‘LiveSolo’ funded by the Austrian Research Promotion Agency (FFG) (project number: 853263).

Keywords: real-time EEG neuroimaging, neurofeedback, stroke, EEG–signal processing, rehabilitation

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Authors: Hakeem Ade Omokayode Idowu

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The extent of the role played by human capabilities developments as well as knowledge management on employees’ performance in the nuclear energy sector of Nigeria remains unclear. This is in view of the important role which human resource capabilities could play in the desire to generate energy using nuclear resources. This study appraised the extent of human resource capabilities available in the nuclear energy sector of Nigeria. It further examined the relationship between knowledge management and employees’ performance in the nuclear energy sector. The study adopted a descriptive research design with a population that comprised all the 1736 members of staff of the selected centres, institutes, and the headquarters of the Nigeria Atomic Energy Commission (NAEC), Nigerian Nuclear Regulatory Authority (NNRA), and Energy Commission of Nigeria (ECN) and a sample size of 332 employees was selected using purposive and convenience sampling techniques. Data collected were subjected to analysis using frequency counts and simple regression. The results showed that majority of the employees perceived that they have to a high extent of availability of knowledge (118, 35.5%), credibility (134, 40.4%), alignment (130, 39.2%), performance (126, 38%) and innovation (138, 41.6%) The result of the hypothesis tested indicated that knowledge management has a positive and significant effect on employees’ performance (Beta weight = 0.336, R2 =0.113, F-value = 41.959, p-value = 0.000< 0.05). The study concluded that human resource capabilities and knowledge management could enhance employee performance within the nuclear energy sector of Nigeria.

Keywords: human resource capabilities, knowledge management, employees productivity, national development

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

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

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

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Authors: Bayole Omoniyi

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This study demonstrates the value of outcrops as analogues for evaluating reservoir quality of sandbody in a typical high-sinuosity fluvial system. The study utilized data acquired from selected outcrops in the Campanian-Maastrichtian siliciclastic succession of the western flank of Anambra Basin, southern Nigeria. Textural properties derived from outcrop samples were correlated and compared with porosity and permeability using established standard charts. Porosity was estimated from thin sections of selected samples to reduce uncertainty in the estimates. Following facies classification, 14 distinct facies were grouped into three facies associations (FA1-FA3) and were subsequently modeled as discrete properties in a block-centered Cartesian grid on a scale that captures geometry of principal sandbodies. Porosity and permeability estimated from charts were populated in the grid using comparable geostatistical techniques that reflect their spatial distribution. The resultant models were conditioned to facies property to honour available data. The results indicate a strong control of geometrical parameters on facies distribution, lateral continuity and connectivity with resultant effect on porosity and permeability distribution. Sand-prone FA1 and FA2 display reservoir quality that varies internally from channel axis to margin in each succession. Furthermore, isolated stack pattern of sandbodies reduces static connectivity and thus, increases risk of poor communication between reservoir-quality sandbodies. FA3 is non-reservoir because it is mud-prone. In conclusion, the risk of poor communication between sandbodies may be effectively accentuated in reservoirs that have similar architecture because of thick lateral accretion deposits, usually mudstone, that tend to disconnect good-quality point-bar sandbodies. In such reservoirs, mudstone may act as a barrier to impede flow vertically from one sandbody to another and laterally at the margins of each channel-fill succession in the system. The development plan, therefore, must be designed to effectively mitigate these risks and the risk of stratigraphic compartmentalization for maximum hydrocarbon recovery.

Keywords: analogues, architecture, connectivity, fluvial

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Authors: Jacob Wahl, Jane Zhang

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This paper describes the development and characterization of a prototype IoT network for use with agricultural imaging and monitoring applications. The sensor and gateway nodes are designed using the ESP32 SoC with integrated Bluetooth Low Energy 4.2 and Wi-Fi. A development board, the Arducam IoTai ESP32, is used for prototyping, testing, and power measurements. Google’s Firebase is used as the cloud storage site for image data collected by the sensor. The sensor node captures images using the OV2640 2MP camera module and transmits the image data to the gateway via Bluetooth Low Energy. The gateway then uploads the collected images to Firebase via a known nearby Wi-Fi network connection. This image data can then be processed and analyzed by computer vision and machine learning pipelines to assess crop growth or other needs. The sensor node achieves a wireless transmission data throughput of 220kbps while consuming 150mA of current; the sensor sleeps at 162µA. The sensor node device lifetime is estimated to be 682 days on a 6600mAh LiPo battery while acquiring five images per day based on the development board power measurements. This network can be utilized by any application that requires high data rates, low power consumption, short-range communication, and large amounts of data to be transmitted at low-frequency intervals.

Keywords: Bluetooth low energy, ESP32, firebase cloud, IoT, smart farming

Procedia PDF Downloads 134

Authors: Chahrazed Salhi, Ayoub Zeroual, Yasmina Hamitouche

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Soil water erosion poses a significant threat to the watersheds in Algeria today. The degradation of storage capacity in large dams over the past two decades, primarily due to erosion, necessitates a comprehensive understanding of the factors that contribute to soil erosion. The Isser watershed, located in the Northwestern region of Algeria, faces additional challenges such as recurrent droughts and the presence of delicate marl and clay outcrops, which amplify its susceptibility to water erosion. This study aims to employ advanced techniques such as Geographic Information Systems (GIS) and Remote Sensing (RS), in conjunction with the Canonical Correlation Analysis (CCA) method and Soil Water Assessment Tool (SWAT) model, to predict specific erosion patterns and analyze the key factors influencing erosion in the Isser basin. To accomplish this, an array of data sources including rainfall, climatic, hydrometric, land use, soil, digital elevation, and satellite data were utilized. The application of the SWAT model to the Isser basin yielded an average annual soil loss of approximately 16 t/ha/year. Particularly high erosion rates, exceeding 12 T/ha/year, were observed in the central and southern parts of the basin, encompassing 41% of the total basin area. Through Canonical Correlation Analysis, it was determined that vegetation cover and topography exerted the most substantial influence on erosion. Consequently, the study identified significant and spatially heterogeneous erosion throughout the study area. The impact of land topography on soil loss was found to be directly proportional, while vegetation cover exhibited an inverse proportional relationship. Modeling specific erosion for the Ladrat dam sub-basin estimated a rate of around 39 T/ha/year, thus accounting for the recorded capacity loss of 17.80% compared to the bathymetric survey conducted in 2019. The findings of this research provide valuable decision-support tools for soil conservation managers, empowering them to make informed decisions regarding soil conservation measures.

Keywords: Isser watershed, RS, CCA, SWAT, vegetation cover, topography

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Authors: Roy. H. A. Lindelauf

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Cyberattacks are complex processes consisting of multiple interwoven tasks conducted by a set of agents. Interdictions and defenses against such attacks often rely on cyber kill chain (CKC) models. A CKC is a framework that tries to capture the actions taken by a cyber attacker. There exists a growing body of literature on CKCs. Most of this work either a) describes the CKC with respect to one or more specific cyberattacks or b) discusses the tools and technologies used by the attacker at each stage of the CKC. Defenders, facing scarce resources, have to decide where to allocate their resources given the CKC and partial knowledge on the tools and techniques attackers use. In this presentation CKCs are analyzed through the lens of covert projects, i.e., interrelated tasks that have to be conducted by agents (human and/or computer) with the aim of going undetected. Various aspects of covert project models have been studied abundantly in the operations research and game theory domain, think of resource-limited interdiction actions that maximally delay completion times of a weapons project for instance. This presentation has investigated both cooperative and non-cooperative game theoretic covert project models and elucidated their relation to CKC modelling. To view a CKC as a covert project each step in the CKC is broken down into tasks and there are players of which each one is capable of executing a subset of the tasks. Additionally, task inter-dependencies are represented by a schedule. Using multi-glove cooperative games it is shown how a defender can optimize the allocation of his scarce resources (what, where and how to monitor) against an attacker scheduling a CKC. This study presents and compares several cooperative game theoretic solution concepts as metrics for assigning resources to the monitoring of agents.

Keywords: cyber defense, cyber kill chain, game theory, information warfare techniques

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Authors: Carlos Alberto Rivera-corredor, Angie Dayana Vargas-Ceballos, Edison Gilpavas, Izabela Dobrosz-Gómez, Miguel Ángel Gómez-García

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Hexavalent chromium, Cr (VI) is present in the effluents from different industries such as electroplating, mining, leather tanning, etc. This compound is of great academic and industrial concern because of its toxic and carcinogenic behavior. Its dumping to both environmental and public health for animals and humans causes serious problems in water sources. The amount of Cr (VI) in industrial wastewaters ranges from 0.5 to 270,000 mgL-1. According to the Colombian standard for water quality (NTC-813-2010), the maximum allowed concentration for the Cr (VI) in drinking water is 0.05 mg L-1. To comply with this limit, it is essential that industries treat their effluent to reduce the Cr (VI) to acceptable levels. Numerous methods have been reported for the treatment removing metal ions from aqueous solutions such as: reduction, ion exchange, electrodialysis, etc. Adsorption has become a promising method for the purification of metal ions in water, since its application corresponds with an economic and efficient technology. The absorbent selection and the kinetic and thermodynamic study of the adsorption conditions are key to the development of a suitable adsorption technology. The Ce0.25Zr0.75O2.nH2O presents higher adsorption capacity between a series of hydrated mixed oxides Ce1-xZrxO2 (x = 0, 0.25, 0.5, 0.75, 1). This work presents the kinetic and thermodynamic study of Cr (VI) adsorption on Ce0.25Zr0.75O2.nH2O. Experiments were performed under the following experimental conditions: initial Cr (VI) concentration = 25, 50 and 100 mgL-1, pH = 2, adsorbent charge = 4 gL-1, stirring time = 60 min, temperature=20, 28 and 40 °C. The Cr (VI) concentration was spectrophotometrically estimated by the method of difenilcarbazide with monitoring the absorbance at 540 nm. The Cr (VI) adsorption over hydrated Ce0.25Zr0.75O2.nH2O models was analyzed using pseudo-first and pseudo-second order kinetics. The Langmuir and Freundlich models were used to model the experimental data. The convergence between the experimental values and those predicted by the model, is expressed as a linear regression correlation coefficient (R2) and was employed as the model selection criterion. The adsorption process followed the pseudo-second order kinetic model and obeyed the Langmuir isotherm model. The thermodynamic parameters were calculated as: ΔH°=9.04 kJmol-1,ΔS°=0.03 kJmol-1 K-1, ΔG°=-0.35 kJmol-1 and indicated the endothermic and spontaneous nature of the adsorption process, governed by physisorption interactions.

Keywords: adsorption, hexavalent chromium, kinetics, thermodynamics

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Authors: Aref Aasi, Sahar Ebrahimi Bajgani, Erfan Aasi

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Breast cancer (BC) continues to be the most frequent cancer in females and causes the highest number of cancer-related deaths in women worldwide. Inspired by recent advances in studying the relationship between different patient attributes and features and the disease, in this paper, we have tried to investigate the different classification methods for better diagnosis of BC in the early stages. In this regard, datasets from the University Hospital Centre of Coimbra were chosen, and different machine learning (ML)-based and neural network (NN) classifiers have been studied. For this purpose, we have selected favorable features among the nine provided attributes from the clinical dataset by using a random forest algorithm. This dataset consists of both healthy controls and BC patients, and it was noted that glucose, BMI, resistin, and age have the most importance, respectively. Moreover, we have analyzed these features with various ML-based classifier methods, including Decision Tree (DT), K-Nearest Neighbors (KNN), eXtreme Gradient Boosting (XGBoost), Logistic Regression (LR), Naive Bayes (NB), and Support Vector Machine (SVM) along with NN-based Multi-Layer Perceptron (MLP) classifier. The results revealed that among different techniques, the SVM and MLP classifiers have the most accuracy, with amounts of 96% and 92%, respectively. These results divulged that the adopted procedure could be used effectively for the classification of cancer cells, and also it encourages further experimental investigations with more collected data for other types of cancers.

Keywords: breast cancer, diagnosis, machine learning, biomarker classification, neural network

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Authors: Lauren C. Porter, Andrew Curtis, Eric Jefferis, Susanne Mitchell

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A wealth of research has been generated examining the variation in crime across neighborhoods. However, there is also a striking degree of crime concentration within neighborhoods. A number of studies show that a small percentage of street segments, intersections, or addresses account for a large portion of crime. Not surprisingly, a focus on these crime hot spots can be an effective strategy for reducing community level crime and related ills, such as health problems. However, research is also limited in an important respect. Studies tend to use official data to identify hot spots, such as 911 calls or calls for service. While the use of call data may be more representative of the actual level and distribution of crime than some other official measures (e.g. arrest data), call data still suffer from the 'dark figure of crime.' That is, there is most certainly a degree of error between crimes that occur versus crimes that are reported to the police. In this study, we present an alternative method of identifying crime hot spots, that does not rely on official data. In doing so, we highlight the potential utility of neighborhood-insiders to identify and understand crime dynamics within geographic spaces. Specifically, we use spatial video and geo-narratives to record the crime insights of 36 police, ex-offenders, and residents of a high crime neighborhood in northeast Ohio. Spatial mentions of crime are mapped to identify participant-identified hot spots, and these are juxtaposed with calls for service (CFS) data. While there are bound to be differences between these two sources of data, we find that one location, in particular, a corner store, emerges as a hot spot for all three groups of participants. Yet it does not emerge when we examine CFS data. A closer examination of the space around this corner store and a qualitative analysis of narrative data reveal important clues as to why this store may indeed be a hot spot, but not generate disproportionate calls to the police. In short, our results suggest that researchers who rely solely on official data to study crime hot spots may risk missing some of the most dangerous places.

Keywords: crime, narrative, video, neighborhood

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Authors: Kamal Amarouche, Houda Benbrahim, Ismail Kassou

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Nowadays, e-commerce shopping websites have experienced noticeable growth. These websites have gained consumers’ trust. After purchasing a product, many consumers share comments where opinions are usually embedded about the given product. Research on the automatic management of opinions that gives suggestions to potential consumers and portrays an image of the product to manufactures has been growing recently. After launching the product in the market, the reviews generated around it do not usually contain helpful information or generic opinions about this product (e.g. telephone: great phone...); in the sense that the product is still in the launching phase in the market. Within time, the product becomes old. Therefore, consumers perceive the advantages/ disadvantages about each specific product feature. Therefore, they will generate comments that contain their sentiments about these features. In this paper, we present an unsupervised method to extract different product features hidden in the opinions which influence its purchase, and that combines Time Weighting (TW) which depends on the time opinions were expressed with Term Frequency-Inverse Document Frequency (TF-IDF). We conduct several experiments using two different datasets about cell phones and hotels. The results show the effectiveness of our automatic feature extraction, as well as its domain independent characteristic.

Keywords: opinion mining, product feature extraction, sentiment analysis, SentiWordNet

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Authors: Mohd Azraei Pangah Pa'at, Mohd Ruzlin Mohd Mokhtar, Norhidayu Rameli, Tashia Marie Anthony, Huzainie Shafi Abd Halim

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Partial Discharge (PD) diagnostic mapping testing is one of the main diagnostic testing techniques that are widely used in the field or onsite testing for underground power cable in medium voltage level. The existence of PD activities is an early indication of insulation weakness hence early detection of PD activities can be determined and provides an initial prediction on the condition of the cable. To effectively manage the results of PD Mapping test, it is important to have acceptable criteria to facilitate prioritization of mitigation action. Tenaga Nasional Berhad (TNB) through Distribution Network (DN) division have developed PD severity model name Severity Index (SI) for offline PD mapping test since 2007 based on onsite test experience. However, this severity index recommendation action had never been revised since its establishment. At presence, PD measurements data have been extensively increased, hence the severity level indication and the effectiveness of the recommendation actions can be analyzed and verified again. Based on the new revision, the recommended action to be taken will be able to reflect the actual defect condition. Hence, will be accurately prioritizing preventive action plan and minimizing maintenance expenditure.

Keywords: partial discharge, severity index, diagnostic testing, medium voltage, power cable

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Authors: John Tarus, Zhendong Niu, Bakhti Khadidja

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In recent years, e-learning recommender systems has attracted great attention as a solution towards addressing the problem of information overload in e-learning environments and providing relevant recommendations to online learners. E-learning recommenders continue to play an increasing educational role in aiding learners to find appropriate learning materials to support the achievement of their learning goals. Although general recommender systems have recorded significant success in solving the problem of information overload in e-commerce domains and providing accurate recommendations, e-learning recommender systems on the other hand still face some issues arising from differences in learner characteristics such as learning style, skill level and study level. Conventional recommendation techniques such as collaborative filtering and content-based deal with only two types of entities namely users and items with their ratings. These conventional recommender systems do not take into account the learner characteristics in their recommendation process. Therefore, conventional recommendation techniques cannot make accurate and personalized recommendations in e-learning environment. In this paper, we propose a recommendation technique combining collaborative filtering and ontology to recommend personalized learning materials to online learners. Ontology is used to incorporate the learner characteristics into the recommendation process alongside the ratings while collaborate filtering predicts ratings and generate recommendations. Furthermore, ontological knowledge is used by the recommender system at the initial stages in the absence of ratings to alleviate the cold-start problem. Evaluation results show that our proposed recommendation technique outperforms collaborative filtering on its own in terms of personalization and recommendation accuracy.

Keywords: collaborative filtering, e-learning, ontology, recommender system

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Authors: Ibrahim A. Adeniran, Rui F. Zhu, Man S. Wong

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Owing to the insufficiency in the spatial representativeness and continuity of in situ temperature measurements from weather stations (WS), the use of temperature measurement from WS for large-range diurnal analysis in heterogenous landscapes has been limited. This has made the accurate estimation of land surface temperature (LST) from remotely sensed data more crucial. Moreover, the study of dynamic interaction between the atmosphere and the physical surface of the Earth could be enhanced at both annual and diurnal scales by using optimal LST data derived from satellite sensors. The tradeoff between the spatial and temporal resolution of LSTs from satellite’s thermal infrared sensors (TIRS) has, however, been a major challenge, especially when high spatiotemporal LST data are recommended. It is well-known from existing literature that polar satellites have the advantage of high spatial resolution, while geostationary satellites have a high temporal resolution. Hence, this study is aimed at designing a framework for the cross-comparison of LST data from polar and geostationary satellites in a heterogeneous landscape. This could help to understand the relationship between the LST estimates from the two satellites and, consequently, their integration in diurnal LST analysis. Landsat-8 satellite data will be used as the representative of the polar satellite due to the availability of its long-term series, while the Himawari-8 satellite will be used as the data source for the geostationary satellite because of its improved TIRS. For the study area, Hong Kong Special Administrative Region (HK SAR) will be selected; this is due to the heterogeneity in the landscape of the region. LST data will be retrieved from both satellites using the Split window algorithm (SWA), and the resulting data will be validated by comparing satellite-derived LST data with temperature data from automatic WS in HK SAR. The LST data from the satellite data will then be separated based on the land use classification in HK SAR using the Global Land Cover by National Mapping Organization version3 (GLCNMO 2013) data. The relationship between LST data from Landsat-8 and Himawari-8 will then be investigated based on the land-use class and over different seasons of the year in order to account for seasonal variation in their relationship. The resulting relationship will be spatially and statistically analyzed and graphically visualized for detailed interpretation. Findings from this study will reveal the relationship between the two satellite data based on the land use classification within the study area and the seasons of the year. While the information provided by this study will help in the optimal combination of LST data from Polar (Landsat-8) and geostationary (Himawari-8) satellites, it will also serve as a roadmap in the annual and diurnal urban heat (UHI) analysis in Hong Kong SAR.

Keywords: automatic weather station, Himawari-8, Landsat-8, land surface temperature, land use classification, split window algorithm, urban heat island

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Authors: Alfonso Ippolito, Cristiana Bartolomei

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A growing demand is felt today for realistic 3D models enabling the cognition and popularization of historical-artistic heritage. Evaluation and preservation of Cultural Heritage is inextricably connected with the innovative processes of gaining, managing, and using knowledge. The development and perfecting of techniques for acquiring and elaborating photorealistic 3D models, made them pivotal elements for popularizing information of objects on the scale of architectonic structures.

Keywords: cultural heritage, databases, non-contact survey, 2D-3D models

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Authors: Sedigheh Samimian, Sadra Ashrafi, Tahereh Khaleghdoost Mohammadi, Mohammad Reza Yeganeh, Ali Ashraf, Hamideh Hakimi, Maryam Dehghani

Abstract:

Introduction: The recommended position for measuring Intra-Abdominal Pressure (IAP) is the supine position. However, patients put in this position are prone to Ventilator-associated pneumonia. This study was done to evaluate the relationship between bed head angle and IAP measurements of intubated patients in the intensive care unit. Methods: In this clinical trial, seventy-six critically ill patients under mechanical ventilation were enrolled. IAP measurement was performed every 8 hours for 24 hours using the KORN method in three different degrees of the head of bed (HOB) elevation (0°, 15°, and 30°). Bland-Altman analysis was performed to identify the bias and limits of agreement among the three HOBs. According to World Society of the Abdominal Compartment Syndrome (WSACS), we can consider two IAP techniques equivalent if a bias of <1 mmHg and limits of agreement of - 4 to +4 were found between them. Data were analyzed using SPSS statistical software (v. 19), and the significance level was considered as 0.05. Results: The prevalence of intra-abdominal hypertension was 18.42%. Mean ± standard deviation (SD) of IAP were 8.44 ± 4.02 mmHg for HOB angle 0°, 9.58 ± 4.52 for HOB angle 15°, and 11.10 ± 4.73 for HOB angle 30o (p = 0.0001). The IAP measurement bias between HOB angle 0◦ and HOB angle 15° was 1.13 mmHg. This bias was 2.66 mmHg between HOB angle 0° and HOB angle 30°. Conclusion: Elevation of HOB angle from 0 to 30 degree significantly increases IAP. It seems that the measurement of IAP at HOB angle 15° was more reliable than 30°.

Keywords: pressure, intra-abdominal hypertension, head of bed, critical care, compartment syndrome, supine position

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Authors: Ruchi Yadav, Shivani Pandey, Prachi Srivastava

Abstract:

Microarrays provide a rich source of data on the molecular working of cells. Each microarray reports on the abundance of tens of thousands of mRNAs. Virtually every human disease is being studied using microarrays with the hope of finding the molecular mechanisms of disease. Bioinformatics analysis plays an important part of processing the information embedded in large-scale expression profiling studies and for laying the foundation for biological interpretation. A basic, yet challenging task in the analysis of microarray gene expression data is the identification of changes in gene expression that are associated with particular biological conditions. Careful statistical design and analysis are essential to improve the efficiency and reliability of microarray experiments throughout the data acquisition and analysis process. One of the most popular platforms for microarray analysis is Bioconductor, an open source and open development software project based on the R programming language. This paper describes specific procedures for conducting quality assessment, visualization and preprocessing of Affymetrix Gene Chip and also details the different bioconductor packages used to analyze affymetrix microarray data and describe the analysis and outcome of each plots.

Keywords: microarray analysis, R language, affymetrix visualization, bioconductor

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Authors: Sateesh Kumar Pisini, Swetha Priya Darshini, Sanjay Kumar Shukla

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This paper seeks to present a research study on sustainability in construction of retaining wall using geosynthetics. Sustainable construction is a way for the building and infrastructure industry to move towards achieving sustainable development, taking into account environmental, socioeconomic and cultural issues. Geotechnical engineering, being very resource intensive, warrants an environmental sustainability study, but a quantitative framework for assessing the sustainability of geotechnical practices, particularly at the planning and design stages, does not exist. In geotechnical projects, major economic issues to be addressed are in the design and construction of stable slopes and retaining structures within space constraints. In this paper, quantitative indicators for assessing the environmental sustainability of retaining wall with geosynthetics are compared with conventional concrete retaining wall through life cycle assessment (LCA). Geosynthetics can make a real difference in sustainable construction techniques and contribute to development in developing countries in particular. Their imaginative application can result in considerable cost savings over the use of conventional designs and materials. The acceptance of geosynthetics in reinforced retaining wall construction has been triggered by a number of factors, including aesthetics, reliability, simple construction techniques, good seismic performance, and the ability to tolerate large deformations without structural distress. Reinforced retaining wall with geosynthetics is the best cost-effective and eco-friendly solution as compared with traditional concrete retaining wall construction. This paper presents an analysis of the theme of sustainability applied to the design and construction of traditional concrete retaining wall and presenting a cost-effective and environmental solution using geosynthetics.

Keywords: sustainability, retaining wall, geosynthetics, life cycle assessment

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Authors: Najrullah Khan, Athar Ali Khan

Abstract:

The Topp-Leone distribution was introduced by Topp- Leone in 1955. In this paper, an attempt has been made to fit Topp-Leone Generalized exponential (TPGE) distribution. A real survival data set is used for illustrations. Implementation is done using R and JAGS and appropriate illustrations are made. R and JAGS codes have been provided to implement censoring mechanism using both optimization and simulation tools. The main aim of this paper is to describe and illustrate the Bayesian modelling approach to the analysis of survival data. Emphasis is placed on the modeling of data and the interpretation of the results. Crucial to this is an understanding of the nature of the incomplete or 'censored' data encountered. Analytic approximation and simulation tools are covered here, but most of the emphasis is on Markov chain based Monte Carlo method including independent Metropolis algorithm, which is currently the most popular technique. For analytic approximation, among various optimization algorithms and trust region method is found to be the best. In this paper, TPGE model is also used to analyze the lifetime data in Bayesian paradigm. Results are evaluated from the above mentioned real survival data set. The analytic approximation and simulation methods are implemented using some software packages. It is clear from our findings that simulation tools provide better results as compared to those obtained by asymptotic approximation.

Keywords: Bayesian Inference, JAGS, Laplace Approximation, LaplacesDemon, posterior, R Software, simulation

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Authors: Shazia Anwer

Abstract:

This paper has discussed the unusual form of resistance in theatre against censorship board in Pakistan. The atypical approach of dramaturgy created massive space for performers and audiences to integrate and communicate. The social and religious absolutes creates suffocation in Pakistani society, strict control over all Fine and Performing Art has made art political, contemporary dramatics has started an amalgamated theatre to avoid censorship. Contemporary Punjabi theatre techniques are directly dependent on human cognition. The idea of indirect thought processing is not unique but dependent on spectators. The paper has provided an account of these techniques and their specific use for conveying specific messages across the audiences. For the Dramaturge of today, theatre space is an expression representing a linguistic formulation that includes qualities of experimental and non-traditional use of classical theatrical space in the context of fulfilling the concept of open theatre. Paper has explained the transformation of the theatrical experience into an event where the actor and the audience are co-existing and co-experiencing the dramatical experience. The denial of the existence of the 4th -Wall made two-way communication possible. This paper has elaborated that the previously marginalized genres such as naach, jugat, miras, are extensively included to counter the censorship board. Figurativeness, visual elements, allegory, scenic imagery are basic support system for contemporary Punjabi theatre. The body of the actor is used as a source for non-verbal communication, and for an escape from traditional theatrical space which by every means has every element that could be controlled and reprimanded by the controlling authority.

Keywords: communication, Punjabi theatre, figurativeness, censorship

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Authors: Vladimir Simovic, Matija Varga, Predrag Oreski

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XHTML and XBRL are the standard languages for creating a database for the purpose of displaying financial statements on web applications. Today, XBRL is one of the most popular languages for business reporting. A large number of countries in the world recognize the role of XBRL language for financial reporting and the benefits that the reporting format provides in the collection, analysis, preparation, publication and the exchange of data (information) which is the positive side of this language. Here we present all advantages and opportunities that a company may have by using the XBRL format for business reporting. Also, this paper presents XBRL and other languages that are used for creating the database, such XML, XHTML, etc. The role of the AJAX complex model and technology will be explained in detail, and during the exchange of financial data between the web client and web server. Here will be mentioned basic layers of the network for data exchange via the web.

Keywords: XHTML, XBRL, XML, JavaScript, AJAX technology, data exchange

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Authors: A. Bari

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Integer programming is a branch of mathematical programming techniques in operations research in which some or all of the variables are required to be integer valued. Various cuts have been used to solve these problems. We have also developed cuts known as NAZ cut & A-T cut to solve the integer programming problems. These cuts are used to reduce the feasible region and then reaching the optimal solution in minimum number of steps.

Keywords: Integer Programming, NAZ cut, A-T cut, Cutting plane method

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Authors: James Sinclair, Katy Soapi, Brad Carte

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The marine environment has continuously demonstrated to be a rich source of secondary metabolites and bioactive compounds that can address the many pharmaceutical problems facing mankind. The emergence of multidrug resistant pathogens has caused scientists to explore contemporary ways of combating these super bugs. A red-pigmented bacterial strain isolated from a marine alga collected in Fiji was identified to be Pseudoalteromonas rubra from 16s rRNA sequencing. This bacterial strain was cultured using a yeast-peptone media and incubated for five days. The ethyl acetate extract of this bacterium was subjected to chromatographic separation techniques such as vacuum liquid chromatography, flash chromatography, size exclusion chromatography and high-pressure liquid chromatography to yield the pure compound and a number of semi-pure fractions. The crude extract and subsequent purified fractions were analyzed by ultraviolet/visible spectroscopy and mass spectroscopy and was found to contain the compounds ivermectin, stenothricin, cyclo-L-pro-L-val, prodigiosin, mycophenolic acid, phenazine-1-carboxylic acid, eplerenone, staurosporine and pseudoalteromone A. The structure of the pure compound, pseudoalteromone A, was elucidated using NMR 1H, 13C, 1H-1H COSY, HSQC and HMBC spectroscopic data.

Keywords: Pseudoalteromonas rubra, Pseudoalteromone A, secondary metabolites, structure elucidation

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Authors: Anna Citterbergova

Abstract:

This study explores the safeguards and guarantees to children’s personal data protection under the current EU and US legislative framework, namely the GDPR (2018) and COPPA (2000). Considering that children are online for the majority of their free time, one cannot overlook the negative side effects that may be associated with online participation, which may put children’s wellbeing and their fundamental rights at risk. The question of whether the current relevant legislative framework in relation to the responsibilities of the internet service providers (ISPs) are adequate safeguards and guarantees to children’s personal data protection has been an evolving debate both in the US and in the EU. From a children’s rights perspective, processors of personal data have certain obligations that must meet the international human rights principles (e. g. the CRC, ECHR), which require taking into account the best interest of the child. Accordingly, the need to protect children’s privacy online remains strong and relevant with the expansion of the number and importance of social media platforms to human life. At the same time, the landscape of the internet is rapidly evolving, and commercial interests are taking a more targeted approach in seeking children’s data. Therefore, it is essential to constantly evaluate the ongoing and evolving newly adopted market policies of ISPs that may misuse the gap in the current letter of the law. Previous studies in the field have already pointed out that both GDPR and COPPA may theoretically not be sufficient in protecting children’s personal data. With the focus on social media platforms, this study uses the doctrinal-descriptive method to identifiy the mechanisms enshrined in the GDPR and COPPA designed to protect children’s personal data. In its second part, the study includes a data gathering phase by the national data protection authorities responsible for monitoring and supervision of the GDPR in relation to children’s personal data protection who monitor the enforcement of the data protection rules throughout the European Union an contribute to their consistent application. These gathered primary source of data will later be used to outline the series of benefits and challenges to children’s persona lata protection faced by these institutes and the analysis that aims to suggest if and/or how to hold ISPs accountable while striking a fair balance between the commercial rights and the right to protection of the personal data of children. The preliminary results can be divided into two categories. First, conclusions in the doctrinal-descriptive part of the study. Second, specific cases and situations from the practice of national data protection authorities. While for the first part, concrete conclusions can already be presented, the second part is currently still in the data gathering phase. The result of this research is a comprehensive analysis on the safeguards and guarantees to children’s personal data protection under the current EU and US legislative framework, based on doctrinal-descriptive approach and original empirical data.

Keywords: personal data of children, personal data protection, GDPR, COPPA, ISPs, social media

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Authors: Sourour Ramzi, Claudia Sarrico

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Little has been done on network DEA in education, and nobody has attempted to model the whole education supply chain using network DEA. As such the contribution of the present paper is to propose a model for measuring the efficiency of education supply chains using network DEA. First, we use a general survey of data envelopment analysis (DEA) to establish the emergent themes for research in DEA, and focus on the theme of Network DEA. Second, we use a survey on two-stage DEA models, and Network DEA to write a state of the art on Network DEA, particularly applied to supply chain management. Third, we use a survey on DEA applications to establish the most influential papers on DEA education applications, in order to establish the state of the art on applications of DEA in education, in general, and applications of DEA to education using network DEA, in particular. Finally, we propose a model for measuring the performance of education supply chains of different education systems (countries or states within a country, for instance). We then use this model on some empirical data.

Keywords: supply chain, education, data envelopment analysis, network DEA

Procedia PDF Downloads 364