Search results for: information warfare techniques

Authors: Diteboho Xaba, Kolentino Mpeta, Tlotliso Qejoe

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This paper assesses the in-sample forecasting of the South African exchange rates comparing a linear ARIMA model and a SETAR model. The study uses a monthly adjusted data of South African exchange rates with 420 observations. Akaike information criterion (AIC) and the Schwarz information criteria (SIC) are used for model selection. Mean absolute error (MAE), root mean squared error (RMSE) and mean absolute percentage error (MAPE) are error metrics used to evaluate forecast capability of the models. The Diebold –Mariano (DM) test is employed in the study to check forecast accuracy in order to distinguish the forecasting performance between the two models (ARIMA and SETAR). The results indicate that both models perform well when modelling and forecasting the exchange rates, but SETAR seemed to outperform ARIMA.

Keywords: ARIMA, error metrices, model selection, SETAR

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Authors: H. Demirtaş, İ. H. Kara, H. Ahlatcı

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Welding failures of steel pipes in power plants usually occur in weld zones. This is similar for the economizer, water walls and superheaters in the power plants where SA 210 Gr. C steel pipes are used. Although these steel pipes have very good welding properties, the welding parameters are also important for the welding life. Welding processes of this pipes are carried out by TIG and SMA techniques. In this study SA 210 Gr. C steel pipes were welded by TIG method and investigated how PWHT affected the welding properties. The results show that this steel does not require post weld heat treatment.

Keywords: SA 210 Gr. C steel pipes, TIG welding, HAZ region, Widmanstatten ferrite

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Authors: Bashir Muhammad

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The present research contains the definition of the internet, the inter-relationship between and globalization as well as the divergent views of scholars on internet net-work. Additionally, both the positive and the negative impacts of the internet on Muslim communities were elucidated. As an example, it is part of the positive effect that the internet constitutes a vital source of vast information and data acquisition in various academic sciences in general and Islamic Studies in particular. The most recent and current facts and scientific discoveries by specialists of various ramifications could be fund as fast as possible. Many other exciting points were also cited. And on the negative side of the internet, among many other points, it releases uncontrolled promiscuous pictures and sometimes misguiding information about Islam, which could gradually and easily destroy the sound moral up bring of our young Muslim generation and pollute their positive thinking and reasoning. Another problem is that, Muslims in most cases pertaining to internet services are passive consumers, having no power to control it and manipulate it for their welfare and well being. Due to that, they have to pay the price for that, directly or indirectly.

Keywords: internet, muslim, challenges, communities

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Authors: Sohini Manna, Jong Woo Kim, Oleg Shpyrko, Eric E. Fullerton

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CVD techniques have emerged as a promising approach in the formation of a broad range of nanostructured materials. The realization of many practical applications will require efficient and economical synthesis techniques that preferably avoid the need for templates or costly single-crystal substrates and also afford process adaptability. Towards this end, we have developed a single-step route for the reduction-type synthesis of nanostructured Ni materials using a thermal CVD method. By tuning the CVD growth parameters, we can synthesize morphologically dissimilar nanostructures including single-crystal cubes and Au nanostructures which form atop untreated amorphous SiO2||Si substrates. An understanding of the new properties that emerge in these nanostructures materials and their relationship to function will lead to for a broad range of magnetostrictive devices as well as other catalysis, fuel cell, sensor, and battery applications based on high-surface-area transition-metal nanostructures. We use coherent X-ray diffraction imaging technique to obtain 3-D image and strain maps of individual nanocrystals. Coherent x-ray diffractive imaging (CXDI) is a technique that provides the overall shape of a nanostructure and the lattice distortion based on the combination of highly brilliant coherent x-ray sources and phase retrieval algorithm. We observe a fine interplay of reduction of surface energy vs internal stress, which plays an important role in the morphology of nano-crystals. The strain distribution is influenced by the metal-substrate interface and metal-air interface, which arise due to differences in their thermal expansion. We find the lattice strain at the surface of the octahedral gold nanocrystal agrees well with the predictions of the Young-Laplace equation quantitatively, but exhibits a discrepancy near the nanocrystal-substrate interface resulting from the interface. The strain in the bottom side of the Ni nanocube, which is contacted on the substrate surface is compressive. This is caused by dissimilar thermal expansion coefficients between Ni nanocube and Si substrate. Research at UCSD support by NSF DMR Award # 1411335.

Keywords: CVD, nanostructures, strain, CXRD

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Authors: Rebecca Oakes

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In the New Zealand public health system, work has been taking place to use electronic systems to convey data from the ‘floor to the board’ that makes patient needs, and therefore nursing work, visible. For nurses, these developments in health information technology puts us in a very new and exciting position of being able to articulate the work of nursing through a language understood at all levels of an organisation, the language of acuity. Nurses increasingly have a considerable stake-hold in patient acuity data. Patient acuity systems, when used well, can assist greatly in demonstrating how much work is required, the type of work, and when it will be required. The New Zealand Safe Staffing Unit is supporting New Zealand nurses to create a culture of shared governance, where nursing data is informing policies, staffing methodologies and forecasting within their organisations. Assisting organisations to understand their acuity data, strengthening user confidence in using electronic patient acuity systems, and ensuring nursing and midwifery workload is accurately reflected is critical to the success of the safe staffing programme. Nurses and midwives have the capacity via an acuity tool to become key informers of organisational planning. Quality patient care, best use of health resources and a quality work environment are essential components of a safe, resilient and well resourced organisation. Nurses are the key informers of this information. In New Zealand a national level approach is paving the way for significant changes to the understanding and use of patient acuity and nursing workload information.

Keywords: nursing workload, patient acuity, safe staffing, New Zealand

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Authors: Nusrat Praween, Krishna Thej Pammi Guru, Palash Kumar Basu

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Designing non-invasive biosensors for cancer diagnosis is essential for developing an affordable and specific tool to measure cancer-related exosome biomarkers. Exosomes, released by healthy as well as cancer cells, contain valuable information about the biomarkers of various diseases, including cancer. Despite the availability of various isolation techniques, ultracentrifugation is the standard technique that is being employed. Post isolation, exosomes are traditionally exposed to detergents for extracting their proteins, which can often lead to protein degradation. Further to this, it is very essential to develop a sensing platform for the quantification of clinically relevant proteins in a wider range to ensure practicality. In this study, exosomes were immobilized on the Au Screen Printed Electrode (SPE) using EDC/NHS chemistry to facilitate binding. After immobilizing the exosomes on the screen-printed electrode (SPE), we investigated the impact of the electric field by applying various voltages to induce exosome lysis and release their contents. The lysed solution was used for sensing TSG101, a crucial biomarker associated with various cancers, using both faradaic and non-faradaic electrochemical impedance spectroscopy (EIS) methods. The results of non-faradaic and faradaic EIS were comparable and showed good consistency, indicating that non-faradaic sensing can be a reliable alternative. Hence, the non-faradaic sensing technique was used for label-free quantification of the TSG101 biomarker. The results were validated using ELISA. Our electrochemical immunosensor demonstrated a consistent response of TSG101 from 125 pg/mL to 8000 pg/mL, with a detection limit of 0.125 pg/mL at room temperature. Additionally, since non-faradic sensing is label-free, the ease of usage and cost of the final sensor developed can be reduced. The proposed immunosensor is capable of detecting the TSG101 protein at low levels in healthy serum with good sensitivity and specificity, making it a promising platform for biomarker detection.

Keywords: biosensor, exosomes isolation on SPE, electric field lysis of exosome, EIS sensing of TSG101

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Authors: Dovile Petkeviciute-Barysiene

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Legal technologies not only create new ways for accessing and providing legal services but also transform the role of legal practitioners. Both lawyers and users of legal services expect automated solutions to outperform people with objectivity and impartiality. Although fairness of the automated decisions is crucial, research on assessing various characteristics of automated processes related to the perceived fairness has only begun. One of the major obstacles to this research is the lack of comprehensive understanding of what legal actions are automated and could be meaningfully automated, and to what extent. Neither public nor legal practitioners oftentimes cannot envision technological input due to the lack of general without illustrative examples. The aim of this study is to map decision making stages and automation levels which are and/or could be achieved in legal actions related to pre-trial and trial processes. Major legal decisions and judgments are identified during the consultations with legal practitioners. The dual-process model of information processing is used to describe cognitive processes taking place while making legal decisions and judgments during pre-trial and trial action. Some of the existing legal technologies are incorporated into the analysis as well. Several published automation level taxonomies are considered because none of them fit well into the legal context, as they were all created for avionics, teleoperation, unmanned aerial vehicles, etc. From the information processing perspective, analysis of the legal decisions and judgments expose situations that are most sensitive to cognitive bias, among others, also help to identify areas that would benefit from the automation the most. Automation level analysis, in turn, provides a systematic approach to interaction and cooperation between humans and algorithms. Moreover, an integrated map of legal decisions and judgments, information processing characteristics, and automation levels all together provide some groundwork for the research of legal technology perceived fairness and acceptance. Acknowledgment: This project has received funding from European Social Fund (project No 09.3.3-LMT-K-712-19-0116) under grant agreement with the Research Council of Lithuania (LMTLT).

Keywords: automation levels, information processing, legal judgment and decision making, legal technology

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Authors: Larissa Bolliger, Junoš Lukan, Mitja Lustrek, Dirk De Bacquer, Els Clays

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Introduction and Aim: Chronic workplace stress and its health-related consequences like mental and cardiovascular diseases have been widely investigated. This project focuses on the sources and context of psychosocial daily workplace stress in a real-world setting. The main objective is to analyze and model real-time relationships between (1) psychosocial stress experiences within the natural work environment, (2) micro-level work activities and events, and (3) physiological signals and behaviors in office workers. Methods: An Ecological Momentary Assessment (EMA) protocol has been developed, partly building on machine learning techniques. Empatica® wristbands will be used for real-life detection of stress from physiological signals; micro-level activities and events at work will be based on smartphone registrations, further processed according to an automated computer algorithm. A field study including 100 office-based workers with high-level problem-solving tasks like managers and researchers will be implemented in Slovenia and Belgium (50 in each country). Data mining and state-of-the-art statistical methods – mainly multilevel statistical modelling for repeated data – will be used. Expected Results and Impact: The project findings will provide novel contributions to the field of occupational health research. While traditional assessments provide information about global perceived state of chronic stress exposure, the EMA approach is expected to bring new insights about daily fluctuating work stress experiences, especially micro-level events and activities at work that induce acute physiological stress responses. The project is therefore likely to generate further evidence on relevant stressors in a real-time working environment and hence make it possible to advise on workplace procedures and policies for reducing stress.

Keywords: ecological momentary assessment, real-time, stress, work

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Authors: Sarah Müller-Sägebrecht

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Today’s volatile environment challenges executives to make the right strategic decisions to gain sustainable success. Entrepreneurship scholars postulate mainly positive effects of environmental changes on entrepreneurship behavior, such as developing new business opportunities, promoting ingenuity, and the satisfaction of resource voids. A strategic solution approach to overcome threatening environmental changes and catch new business opportunities is business model innovation (BMI). Although this research stream has gained further importance in the last decade, BMI research is still insufficient. Especially BMI barriers, such as inefficient strategic decision-making processes, need to be identified. Strategic decisions strongly impact organizational future and are, therefore, usually made in groups. Although groups draw on a more extensive information base than single individuals, group-interaction effects can influence the decision-making process - in a favorable but also unfavorable way. Decisions are characterized by uncertainty and risk, whereby their intensity is perceived individually differently. Individual risk-willingness influences which option humans choose. The special nature of strategic decisions, such as in BMI processes, is that these decisions are not made individually but in groups due to their high organizational scope. These groups consist of different personalities whose individual risk-willingness can vary considerably. It is known from group decision theory that these individuals influence each other, observable in different group-interaction effects. The following research questions arise: i) Which impact has the individual risk-willingness on BMI decisions? And ii) how do group interaction effects impact BMI decisions? After conducting 26 in-depth interviews with executives from the manufacturing industry, the applied Gioia methodology reveals the following results: i) Risk-averse decision-makers have an increased need to be guided by facts. The more information available to them, the lower they perceive uncertainty and the more willing they are to pursue a specific decision option. However, the results also show that social interaction does not change the individual risk-willingness in the decision-making process. ii) Generally, it could be observed that during BMI decisions, group interaction is primarily beneficial to increase the group’s information base for making good decisions, less than for social interaction. Further, decision-makers mainly focus on information available to all decision-makers in the team but less on personal knowledge. This work contributes to strategic decision-making literature twofold. First, it gives insights into how group-interaction effects influence an organization’s strategic BMI decision-making. Second, it enriches risk-management research by highlighting how individual risk-willingness impacts organizational strategic decision-making. To date, it was known in BMI research that risk aversion would be an internal BMI barrier. However, with this study, it becomes clear that it is not risk aversion that inhibits BMI. Instead, the lack of information prevents risk-averse decision-makers from choosing a riskier option. Simultaneously, results show that risk-averse decision-makers are not easily carried away by the higher risk-willingness of their team members. Instead, they use social interaction to gather missing information. Therefore, executives need to provide sufficient information to all decision-makers to catch promising business opportunities.

Keywords: business model innovation, decision-making, group biases, group decisions, group-interaction effects, risk-willingness

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Authors: Misho Matsankov, Stoyan Petrov

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The paper presents the methodology and the obtained mathematical models for determining the value of the grounding resistance of a disconnected conductor in a three-phase power line, for which the contact voltage is safe, by taking into account the potentials, induced by the non-disconnected phase conductors. The mathematical models have been obtained by implementing the experimental design techniques.

Keywords: contact voltage, experimental design, induced voltage, safety

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Authors: Diego Saldo Alves, Marcelo Paveck Ayub

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The quality of accounting information is very important for the decision-making of managers, investors government and other information users. The opinion of the independent audit has a significant influence on the decision-making, especially the investors. Therefore, the aim of this study is to analyze the reasons that companies listed on Brazilian Stock Exchange B3, if they received qualified opinion and disclaimer of opinion of the independent auditors. We analyzed the reports of the independent auditors of 23 Brazilian companies listed in B3 that received qualified opinion and disclaimer of opinion between the years 2012 and 2017. The findings show that the companies do not comply the International Financial Reporting Standard, IFRS, also they did not provide documentation to prove the operations performed, did not account expenses, problems in corporate governance and internal controls.

Keywords: audit, disclaimer of opinion, independent auditors, qualified opinion

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Authors: Faiza Hussain, Usman Qamar

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Synonym-based searching is recognized to be a complicated problem as text mining from unstructured data of web is challenging. Finding useful information which matches user need from bulk of web pages is a cumbersome task. In this paper, a novel and practical synonym retrieval technique is proposed for addressing this problem. For replacement of semantics, user intent is taken into consideration to realize the technique. Parts-of-Speech tagging is applied for pattern generation of the query and a thesaurus for this experiment was formed and used. Comparison with Non-Context Based Searching, Context Based searching proved to be a more efficient approach while dealing with linguistic semantics. This approach is very beneficial in doing intent based searching. Finally, results and future dimensions are presented.

Keywords: natural language processing, text mining, information retrieval, parts-of-speech tagging, grammar, semantics

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Authors: A. Ashraff

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The increasing importance of the web as a medium for electronic and business transactions has served as a catalyst or rather a driving force for the introduction and implementation of recommender systems. Recommender Systems play a major role in processing and analyzing thousands of data rows or reviews and help humans make a purchase decision of a product or service. It also has the ability to predict whether a particular user would rate a product or service based on the user’s profile behavioral pattern. At present, Recommender Systems are being used extensively in every domain known to us. They are said to be ubiquitous. However, in the field of recruitment, it’s not being utilized exclusively. Recent statistics show an increase in staff turnover, which has negatively impacted the organization as well as the employee. The reasons being company culture, working flexibility (work from home opportunity), no learning advancements, and pay scale. Further investigations revealed that there are lacking guidance or support, which helps a job seeker find the company that will suit him best, and though there’s information available about companies, job seekers can’t read all the reviews by themselves and get an analytical decision. In this paper, we propose an approach to study the available review data on IT companies (score their reviews based on user review sentiments) and gather information on job seekers, which includes their Psychometric evaluations. Then presents the job seeker with useful information or rather outputs on which company is most suitable for the job seeker. The theoretical approach, Algorithmic approach and the importance of such a system will be discussed in this paper.

Keywords: psychometric tests, recommender systems, sentiment analysis, hybrid recommender systems

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Authors: Jaehyung An, Sungjoo Lee

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Patent documents constitute an up-to-date and reliable source of knowledge for reflecting technological advance, so patent analysis has been widely used for identification of technological trends and formulation of technology strategies. But, identifying technological information from patent data entails some limitations such as, high cost, complexity, and inconsistency because it rely on the expert’ knowledge. To overcome these limitations, researchers have applied to a quantitative analysis based on the keyword technique. By using this method, you can include a technological implication, particularly patent documents, or extract a keyword that indicates the important contents. However, it only uses the simple-counting method by keyword frequency, so it cannot take into account the sematic relationship with the keywords and sematic information such as, how the technologies are used in their technology area and how the technologies affect the other technologies. To automatically analyze unstructured technological information in patents to extract the semantic information, it should be transformed into an abstracted form that includes the technological key concepts. Specific sentence structure ‘SAO’ (subject, action, object) is newly emerged by representing ‘key concepts’ and can be extracted by NLP (Natural language processor). An SAO structure can be organized in a problem-solution format if the action-object (AO) states that the problem and subject (S) form the solution. In this paper, we propose the new methodology that can extract the SAO structure through technical elements extracting rules. Although sentence structures in the patents text have a unique format, prior studies have depended on general NLP (Natural language processor) applied to the common documents such as newspaper, research paper, and twitter mentions, so it cannot take into account the specific sentence structure types of the patent documents. To overcome this limitation, we identified a unique form of the patent sentences and defined the SAO structures in the patents text data. There are four types of technical elements that consist of technology adoption purpose, application area, tool for technology, and technical components. These four types of sentence structures from patents have their own specific word structure by location or sequence of the part of speech at each sentence. Finally, we developed algorithms for extracting SAOs and this result offer insight for the technology innovation process by providing different perspectives of technology.

Keywords: NLP, patent analysis, SAO, semantic-analysis

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Authors: Mbida Mohamed, Ezzati Abdellah

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A strong challenge in the wireless sensor networks (WSN) is to save the energy and have a long life time in the network without having a high rate of loss information. However, topology control (TC) protocols are designed in a way that the network is divided and having a standard system of exchange packets between nodes. In this article, we will propose a clustering based and centralized routing table protocol of TC (CBCRT) which delegates a leader node that will encapsulate a single routing table in every cluster nodes. Hence, if a node wants to send packets to the sink, it requests the information's routing table of the current cluster from the node leader in order to root the packet.

Keywords: mobile wireless sensor networks, routing, topology of control, protocols

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Authors: Mohammad Esmaeilpour

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One of the important open problems in the field of medical image processing is detection and quantification of small changes. In this poster, we try to investigate that, how the algebraic decomposition techniques can be used for semiautomatically detecting and quantifying subtle changes in Magnetic Resonance (MR) neuroimaging volumes. We mostly focus on the low-rank values of the matrices achieved from decomposing MR image pairs during a period of time. Besides, a skillful neuroradiologist will help the algorithm to distinguish between noises and small changes.

Keywords: magnetic resonance neuroimaging, subtle change detection and quantification, algebraic decomposition, basis functions

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Authors: Shu Tao

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Based on a global fuel consumption data product (PKU-FUEL-2007) compiled recently and a series of databases for emission factors of various sources, global emission inventories of a number of greenhouse gases and air pollutants, including CO2, CO, SO2, NOx, primary particulate matter (total, PM 10, and PM 2.5), black carbon, organic carbon, mercury, volatile organic carbons, and polycyclic aromatic hydrocarbons, from combustion sources have been developed. The inventories feather high spatial and sectorial resolutions. The spatial resolution of the inventories are 0.1 by 0.1 degree, based on a sub-national disaggregation approach to reduce spatial bias due to uneven distribution of per person fuel consumption within countries. The finely resolved inventories provide critical information for chemical transport modeling and exposure modeling. Emissions from more than 60 sources in energy, industry, agriculture, residential, transportation, and wildfire sectors were quantified in this study. With the detailed sectorial information, the inventories become an important tool for policy makers. For residential sector, a set of models were developed to simulate temporal variation of fuel consumption, consequently pollutant emissions. The models can be used to characterize seasonal as well as inter-annual variations in the emissions in history and to predict future changes. The models can even be used to quantify net change of fuel consumption and pollutant emissions due to climate change. The inventories has been used for model ambient air quality, population exposure, and even health effects. A few examples of the applications are discussed.

Keywords: air pollutants, combustion, emission inventory, sectorial information

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Authors: Abdul Ghani Rajput

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Although monitoring and evaluation concept adopted by Technical Vocational Education and Training (TVET) organization to track the progress over the continuous interval of time based on planned interventions and subsequently, evaluating it for the impact, quality assurance and sustainability. In digital world, TVET providers are giving preference to have real time information to do monitoring of training activities. Identifying the benefits and challenges of digitized monitoring & evaluation real time information system has not been sufficiently tackled in this date. This research paper looks at the impact of digitized M&E in TVET sector by analyzing two case studies and describe the benefits and challenges of using digitized M&E system. Finally, digitized M&E have been identified as carriers for high potential of TVET sector.

Keywords: digitized M&E, innovation, quality assurance, TVET

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Authors: Christopher Reichstein, Ralf-Christian Härting, Martina Häußler

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With a continuously increasing speed of information exchange on the World Wide Web, retailers in the E-Commerce sector are faced with immense possibilities regarding different online purchase processes like dynamic price settings. By use of Dynamic Pricing, retailers are able to set short time price changes in order to optimize producer surplus. The empirical research illustrates the basics of Dynamic Pricing and identifies six influencing factors of Dynamic Pricing. The results of a structural equation modeling approach show five main drivers increasing the potential of dynamic price settings in the E-Commerce. Influencing factors are the knowledge of customers’ individual willingness to pay, rising sales, the possibility of customization, the data volume and the information about competitors’ pricing strategy.

Keywords: e-commerce, empirical research, experts, dynamic pricing (DP), influencing factors, potentials

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Authors: Sergio Zabala-Vargas, Miguel Jiménez-Barrera, Luz VArgas-Sánchez

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In recent years, information related to project management in organizations has been increasing exponentially. Performance data, management statistics, indicator results have forced the collection, analysis, traceability, and dissemination of project managers to be essential. In this sense, there are current trends to facilitate efficient decision-making in emerging technology projects, such as: Machine Learning, Data Analytics, Data Mining, and Big Data. The latter is the most interesting in this project. This research is part of the thematic line Construction methods and project management. Many authors present the relevance that the use of emerging technologies, such as Big Data, has taken in recent years in project management in the construction sector. The main focus is the optimization of time, scope, budget, and in general mitigating risks. This research was developed in the northeastern region of Colombia-South America. The first phase was aimed at diagnosing the use of emerging technologies (Big-Data) in the construction sector. In Colombia, the construction sector represents more than 50% of the productive system, and more than 2 million people participate in this economic segment. The quantitative approach was used. A survey was applied to a sample of 91 companies in the construction sector. Preliminary results indicate that the use of Big Data and other emerging technologies is very low and also that there is interest in modernizing project management. There is evidence of a correlation between the interest in using new data management technologies and the incorporation of Building Information Modeling BIM. The next phase of the research will allow the generation of guidelines and strategies for the incorporation of technological tools in the construction sector in Colombia.

Keywords: big data, building information modeling, tecnology, project manamegent

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Authors: Roger Yu

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A numerical scheme has been developed to solve wave equations for chaotic systems such as stadium-shaped cavity. The same numerical method can also be used for finding wave properties of rectangle cavities with randomly placed obstacles. About 30k eigenvalues have been obtained accurately on a normal circumstance. For comparison, we also initiated an experimental study which determines both eigenfrequencies and eigenfunctions of a stadium-shaped cavity using pulse and normal mode analyzing techniques. The acoustic cavity was made adjustable so that the transition from nonchaotic (circle) to chaotic (stadium) waves can be investigated.

Keywords: quantum dot, chaos, numerical method, eigenvalues

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Authors: Ehsan Kadkhodaie, Shahin Parvar, Soroush Senemar, Mostafa Shriat, Abdolrasoul Malekpour

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The role of oil in supra distribution transformers is so critical and, several standards in determining the quality of oil have been offered. So far, moisture, viscosity and insulation protection of the oil have been measured based on mechanical and chemical methods and systems such as kart fisher, falling ball and TDM 4000 that most of these techniques are destructive and have many problems such as pollution. In this study, due to the properties of oil and also physical behavior of ultrasound wave new method was designed to in the determination of oil indicators including viscosity and moisture. The results show the oil viscosity can be found from the relationship μ = 42.086/√EE and moisture from (PLUS+) = −15.65 (PPM) + 26040 relationship.

Keywords: oil, viscosity, moisture, ultrasonic waves

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Authors: Abderrahim Siam, Ramdane Maamri, Zaidi Sahnoun

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The development of adaptive user interfaces (UI) presents for a long time an important research area in which researcher attempt to call upon the full resources and skills of several disciplines. The adaptive UI community holds a thorough knowledge regarding the adaptation of UIs with users and with contexts of use. Several solutions, models, formalisms, techniques, and mechanisms were proposed to develop adaptive UI. In this paper, we propose an approach based on the fuzzy set theory for modeling the concept of the appropriateness of different solutions of UI adaptation with different situations for which interactive systems have to adapt their UIs.

Keywords: adaptive user interfaces, adaptation solution’s appropriateness, fuzzy sets

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Authors: Daniel Brian Thompson, Subarmaniam Kannan

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The huge weightage of knowledge in this world and within the repository of organizations has already reached immense capacity and is constantly increasing as time goes by. To accommodate these constraints, Big Data implementation and algorithms are utilized to obtain new or enhanced knowledge for decision-making. With the transition from data to knowledge provides the transformational changes which will provide tangible benefits to the individual implementing these practices. Today, various organization would derive knowledge from observations and intuitions where this information or data will be translated into best practices for knowledge acquisition, generation and sharing. Through the widespread usage of Big Data, the main intention is to provide information that has been cleaned and analyzed to nurture tangible insights for an organization to apply to their knowledge-creation practices based on facts and figures. The translation of data into knowledge will generate value for an organization to make decisive decisions to proceed with the transition of best practices. Without a strong foundation of knowledge and Big Data, businesses are not able to grow and be enhanced within the competitive environment.

Keywords: big data, knowledge management, data driven, knowledge creation

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Authors: Laila Yasir Al-Harthy, Ali H. Al-Badi

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As an emerging business model, cloud computing has been initiated to satisfy the need of organizations and to push Information Technology as a utility. The shift to the cloud has changed the way Information Technology departments are managed traditionally and has raised many concerns for both, public and private sectors. The purpose of this study is to investigate the possibility of cloud computing services replacing services provided traditionally by IT departments. Therefore, it aims to 1) explore whether organizations in Oman are ready to move to the cloud; 2) identify the deciding factors leading to the adoption or rejection of cloud computing services in Oman; and 3) provide two case studies, one for a successful Cloud provider and another for a successful adopter. This paper is based on multiple research methods including conducting a set of interviews with cloud service providers and current cloud users in Oman; and collecting data using questionnaires from experts in the field and potential users of cloud services. Despite the limitation of bandwidth capacity and Internet coverage offered in Oman that create a challenge in adopting the cloud, it was found that many information technology professionals are encouraged to move to the cloud while few are resistant to change. The recent launch of a new Omani cloud service provider and the entrance of other international cloud service providers in the Omani market make this research extremely valuable as it aims to provide real-life experience as well as two case studies on the successful provision of cloud services and the successful adoption of these services.

Keywords: cloud computing, cloud deployment models, cloud service models, deciding factors

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Authors: Masaya Yoshikawa, Toshiya Asai, Ryoma Matsuhisa, Yusuke Nozaki, Kensaku Asahi

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Recently, side-channel attacks, which estimate secret keys using side-channel information such as power consumption and compromising emanations of cryptography circuits embedded in hardware, have become a serious problem. In particular, electromagnetic analysis attacks against cryptographic circuits between information processing and electromagnetic fields, which are related to secret keys in cryptography circuits, are the most threatening side-channel attacks. Therefore, it is important to evaluate tamper resistance against electromagnetic analysis attacks for cryptography circuits. The present study performs basic examination of the tamper resistance of cryptography circuits using electromagnetic analysis attacks with noise resources.

Keywords: tamper resistance, cryptographic circuit, hardware security evaluation, noise resources

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Authors: Edlira Kalemi, Sule Yildirim-Yayilgan

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Online Social Networks (OSNs) are nowadays being used widely and intensively for crime investigation and prevention activities. As they provide a lot of information they are used by the law enforcement and intelligence. An extensive review on existing solutions and models for collecting intelligence from this source of information and making use of it for solving crimes has been presented in this article. The main focus is on smart solutions and models where ontologies have been used as the main approach for representing criminal domain knowledge. A framework for a prototype ontology named SC-Ont will be described. This defines terms of the criminal domain ontology and the relations between them. The terms and the relations are extracted during both this review and the discussions carried out with domain experts. The development of SC-Ont is still ongoing work, where in this paper, we report mainly on the motivation for using smart ontology models and the possible benefits of using them for solving crimes.

Keywords: criminal digital evidence, social media, ontologies, reasoning

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Authors: Mohammad Julhas Sujan, Md. Ferdous Alam

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Maternal, neonatal, and child health (MNCH) holds one of the prime focuses in Bangladesh’s national healthcare system. To save the lives of mothers and children, knowing the stock of MNCH medicines in different healthcare facilities and when to replenish them are essential. A robust information system not only facilitates efficient management of the essential MNCH medicines but also helps effective allocation of scarce resources. In Bangladesh, Supply chain management of the 25-essential life-saving medicines are currently tracked and monitored via an electronic logistics management information system (eLMIS). Our aim was to conduct a cross-sectional study with a year (2020) worth of data from 24 districts of Bangladesh to evaluate how eLMIS is helping the Government and other stakeholders in efficient supply chain management. Data were collected from 4711 healthcare facilities ranging from primary to secondary levels within a district. About 90% (4143) are community clinics which are considered primary health care facilities in Bangladesh. After eLMIS implementation, the average reporting rate across the districts has been increased (> 97%). The month of stock (MOS) of zinc is an average 6 months compared to Inj. Magnesium Sulphate which will take 2.5 years to consume according to the current average monthly consumption (AMC). Due to first approaching expiry, Tab. Misoprostol, 7.1% Chlorhexidine and Inj. Oxytocin may become unusable. Moreover, Inj. Oxytocin is temperature sensitive and may reduce its efficacy if it is stocked for a longer period. In contrast, Zinc should be sufficiently stocked to prevent sporadic stockouts. To understand how data are collected, transmitted, processed, and aggregated for MNCH medicines in a faster and timely manner, an electronic logistics management information system (eLMIS) is necessary. We recommend the use of such a system in developing countries like Bangladesh for efficient supply chain management of essential MNCH medicines.

Keywords: adaption, eLMIS, MNCH, live-saving medicines

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Authors: Natàlia Garcia Soler, Timothy Moss

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Despite the multiple benefits of sustainable urban drainage, as demonstrated in numerous case studies across the world, urban rainwater harvesting techniques are generally restricted to isolated model projects. The leap from niche to mainstream has, in most cities, proved an elusive goal. Why policies promoting rainwater harvesting are limited in their widespread implementation has seldom been subjected to systematic analysis. Much of the literature on the policy, planning and institutional contexts of these techniques focus either on their potential benefits or on project design, but very rarely on a critical-constructive analysis of past experiences of implementation. Moreover, the vast majority of these contributions are restricted to single-case studies. There is a dearth of knowledge with respect to, firstly, policy implementation processes and, secondly, multi-case analysis. Insights from both, the authors argue, are essential to inform more effective rainwater harvesting in cities in the future. This paper presents preliminary findings from a research project on rainwater harvesting in cities from a social science perspective that is funded by the Swedish Research Foundation (Formas). This project – UrbanRain – is examining the challenges and opportunities of mainstreaming rainwater harvesting in three European cities. The paper addresses two research questions: firstly, what lessons can be learned on suitable policy incentives and planning instruments for rainwater harvesting from a meta-analysis of the relevant international literature and, secondly, how far these lessons are reflected in a study of past and ongoing rainwater harvesting projects in a European forerunner city. This two-tier approach frames the structure of the paper. We present, first, the results of the literature analysis on policy and planning issues of urban rainwater harvesting. Here, we analyze quantitatively and qualitatively the literature of the past 15 years on this topic in terms of thematic focus, issues addressed and key findings and draw conclusions on research gaps, highlighting the need for more studies on implementation factors, actor interests, institutional adaptation and multi-level governance. In a second step we focus in on the experiences of rainwater harvesting in Berlin and present the results of a mapping exercise on a wide variety of projects implemented there over the last 30 years. Here, we develop a typology to characterize the rainwater harvesting projects in terms of policy issues (what problems and goals are targeted), project design (which kind of solutions are envisaged), project implementation (how and when they were implemented), location (whether they are in new or existing urban developments) and actors (which stakeholders are involved and how), paying particular attention to the shifting institutional framework in Berlin. Mapping and categorizing these projects is based on a combination of document analysis and expert interviews. The paper concludes by synthesizing the findings, identifying how far the goals, governance structures and instruments applied in the Berlin projects studied reflect the findings emerging from the meta-analysis of the international literature on policy and planning issues of rainwater harvesting and what implications these findings have for mainstreaming such techniques in future practice.

Keywords: institutional framework, planning, policy, project implementation, urban rainwater management

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Authors: Sepulveda Juan

Abstract:

This article explains the elements and considerations taken into account when implementing and applying patent evaluation and scientometric study in the identifications of technology trends, and the tools that led to the implementation of a software application for patent revision. Univariate analysis helped recognize the technological leaders in the field of energy, and steered the way for a multivariate analysis of this sample, which allowed for a graphical description of the techniques of mature technologies, as well as the detection of emerging technologies. This article ends with a validation of the methodology as applied to the case of fuel cells.

Keywords: patents, scientometric, renewable energy, technology maps

Procedia PDF Downloads 300