Showing papers presented at "International Conference on Innovations in Information Technology in 2016"

Internet of things: Applications and challenges

Abstract: The keyword ‘Internet of Things’ (IoT) is used to refer to many concepts related to the extension of the Internet and the Web into the physical daily life. This is supported by means of the widespread of distributed devices with embedded identification, sensing and/or actuation capabilities. IoT envisions a future in which both digital and physical entities can be linked, by means of appropriate information and communication technologies, to enable a big range of applications and services. In this article, I will highlight some details of these technologies, applications and research challenges for IoT.

Facial features monitoring for real time drowsiness detection

Abstract: This paper describes an efficient method for drowsiness detection by three well defined phases. These three phases are facial features detection using Viola Jones, the eye tracking and yawning detection. Once the face is detected, the system is made illumination invariant by segmenting the skin part alone and considering only the chromatic components to reject most of the non face image backgrounds based on skin color. The tracking of eyes and yawning detection are done by correlation coefficient template matching. The feature vectors from each of the above phases are concatenated and a binary linear support vector machine classifier is used to classify the consecutive frames into fatigue and nonfatigue states and sound an alarm for the former, if it is above the threshold time. Extensive real time experiments prove that the proposed method is highly efficient in finding the drowsiness and alerting the driver.

Challenges and opportunities for underwater sensor networks

Abstract: Wireless sensor networks (WSN) are distributed event-based systems comprising of tiny nodes capable of sensing the environmental phenomena with a limited battery, low pro­cessing power and short-range radio for communication. Most of the applications of sensor network are concerned with sensing scalar sensor such as temperature, pressure, humidity, or location of objects that can be conveyed through low-bandwidth and delay-tolerant data streams. More than a decade's research has matured communication protocols, sensor technology, bandwidth, energy efficiency and lifetime of traditional WSNs. The recent interest in underwater wireless sensor networks (UWSN) has resulted in various technological advances in the domain as well however, these advances have faced many challenges that are not seen in traditional WSNs. This paper discusses the technical challenges and available technologies that can be used to establish an underwater sensor network solution for applications such as monitoring of coral reefs.

An adaptive Kalman filter based traffic prediction algorithm for urban road network

Abstract: Frequent traffic congestion and gridlocks are causing global economies staggering cost in terms of fuel consumption, time wastage, and public health. To rectify this problem, many advocates combining Information and Communication Technologies (ICT) and traffic engineering concepts for better traffic management. Timely and accurate traffic prediction and management are central to the ICT-based Intelligent Transportation Systems (ITS). In this paper, we presented a traffic prediction model based on Kalman filtering theory, which optimizes the prediction of speed by minimizing the variance between the real-time speed measurement and its estimation. The prediction model predicts the speed across high-level roadway segments using historical and real-time speed measurements (spot speed) reported by the vehicles traveling on the urban road network. The performance evaluation of the proposed prediction model includes a number of case studies. Each case study is conducted with different parametric settings to explain the different characteristic of the model. The results show that provided the spot speed measurements don't fluctuate significantly over the time, the proposed model is capable of predicting traffic with 54% more accuracy.

From the Internet of Things to the web of things — enabling by sensing as-a service

Abstract: Sensing as a Service (SenaaS) is emerging as a prominent element in the middleware linking together the Internet of Things (IoT) and the Web of Things (WoT) layers of future ubiquitous systems. An architecture framework is discussed in this paper whereby things are abstracted into services via embedded sensors which expose a thing as a service. The architecture acts as a blueprint to guide software architects realizing WoT applications. Web-enabled things are eventually appended into Web platforms such as Social Web platforms to drive data and services that are exposed by these things to interact with both other things and people, in order to materialize further the future social Web of Things. Research directions are discussed to illustrate the integration of SenaaS into the proposed WoT architectural framework.

Review of personalized language learning systems

Abstract: This study reviews published scientific literature on personalized language learning systems. The focus is threefold: 1) present a review and categorization framework that can be used to analyze and classify personalized language learning systems, 2) analyze recent work in personalized language learning systems and organize them under the proposed framework, 3) identify current trends, challenges and open research questions in the field. Our review led us to propose a review and classification scheme with two dimensions each with a few sub-elements: language learning dimension and technical dimension. The reviewed articles indicate that recent language personalization systems increasingly introduce Artificial Intelligence and focus on cognitive-based personalization. Findings also suggest that language personalization systems may improve by incorporating more complex adaptive learner's model and more complex contextual language learning tasks.

Reconfigurable triple notched-band ultra wideband antenna

Abstract: In this paper, a reconfigurable triple notched-band UWB (Ultra Wide Band) antenna is presented. This compact antenna covers the frequency range from 3.1 GHz to 11.21 GHz. In order to reject a three frequency bands including the WiMAX (3.2–3.6 GHz), WLAN (5.15–5.85 GHz) and X band (7.25–8.395 GHz), we have inserted three different slots in the radiating patch; two C-shaped slots and a rectangular slot. To achieve the reconfiguration in the notched-band antenna, we have added a PIN diode in every slot to control these slots. The proposed antenna has a size of 30×30 mm2. The simulated results show a bandwidth with VSWR less than 2 and the radiation pattern is Omni-directional in XZ plane and bidirectional in YZ plane.

The use of data mining techniques to predict mortality and length of stay in an ICU

Abstract: Data mining is commonly used in the healthcare industry and managing Intensive Care Unit (ICU) is no exception. This study aims to examine how data mining techniques can be employed to predict mortality and length of stay in an ICU and to evaluate various classification techniques. Real-life healthcare datasets, like MIMIC 2, incorporate an unbalanced distribution of sample sizes, which means that it is difficult to employ them to assess classification. This paper presents an analysis of a mortality prediction algorithm to evaluate the extent to which this algorithm can predict mortality rate. The model aims to facilitate the process by which medical practitioners provide customized and optimized care in the ICU.

Analysis of free-text keystroke dynamics for Arabic language using Euclidean distance

Abstract: Online services play an increasingly important role in executing tasks in many aspects of our lives. These services depend greatly on authentication mechanisms in order to give sufficient protection to the provided data. Since the traditional username and password scheme suffers from various security and usability drawbacks, this paper investigates a free-text keystroke dynamic authentication approach which provides security with high level of usability. In particular, this study extends previous studies in which the Arabic language is incorporated by investigating the utilization of different timing features, as well as applying Euclidean distance classification method. Based on a controlled experiment, the False Accept Rates (FAR) was 0.2, while the False Reject Rates (FRR) was 0.0. The results showed that the system performance is enhanced compared to other studies.

Overview of ICT in the advancement of electric vehicle penetration: Overview of vehicle grid communication system and charging infrastructure and a case study of economic and environmental benefits of electric vehicles in Nebraska

Abstract: Information and communication technology (ICT) plays a key role in our society, making management and planning easier across sectors. ICT can also help users during times of transition to promote a newer technology in an industry, such as transportation, and aid in GHG reductions by its enabling technologies. Battery electric vehicles (BEV) emit less CO2 than conventional vehicles, offering a way to lower fuel emissions. The sales of BEVs have shown a strong growth trend in the U.S., but continued use depends on effective ICT based enabling technologies to link BEVs with its environment to provide information such as real-time battery charge levels, location of nearest charging infrastructure, route options to optimize battery performance and energy price in a given area within the BEVs vehicle grid communication (VGC) infrastructure. In an effort to build BEV charging infrastructure aided by ICT enabling technologies to promote and deploy BEV, a case study is presented in which 24 BEVs and 35 Chargepoint charging stations are deployed across communities in Nebraska. Data analysis is used to gain insight into charging times, user charging habits, economic and environmental saving, information that can be used by ICT enabling technologies to optimize the user experience, smart grid operation and wide spread adoption of BEVs.

Ensemble classification of cyber space users tendency in blog writing using random forest

Abstract: As blogs widely spread, the need to extract information is necessary in order to deal with different issues such as social, political, criminal and others. This research takes off from Gharehchopogh et al. [2], [3] who used the C4.5 and K-Nearest Neighbor (K-NN) algorithms to classify bloggers whether they are professional or otherwise from the Kohkilooyeh and Boyer Ahmad province in Iran. As a comparative measure, this paper proposed the Random Forest algorithm to perform the blog classification using the same dataset. The results showed that ensemble classification via Random Forest algorithm is able to produce higher precision of 88% as compared to 82% by the C4.5 algorithm and 84% by K-NN in the previous research.

SADSA: Security aware distribution system architecture for smart grid applications

Abstract: The distribution system is one of the main components in a a smart grid, readings are transferred from the distribution substations to the control center. Compromising system data will result in drawing wrong conclusions about current operation status at the control center, and subsequently, sending wrong commands, which may result in very serious consequences. In this paper, we propose a scalable communications architecture for future smart grid distribution systems (i.e. SADSA). The architecture is adaptable to use WiFi or other technologies to transfer smart grid information. The architecture is studied from various angles. Both communication and cybersecurity challenges are extracted. In addition, the paper provides a detailed discussion on how the proposed architecture meets National Institute of Standards and Technology (NIST) security requirements for smart grids.

Lightweight encryption algorithm in wireless body area network for e-health monitoring

Abstract: There is an increase in the diseases of the circulatory system in United Arab Emirates, which makes it the first leading cause of death. Therefore, there is a high demand for a continuous care that can be achieved by adopting an emerging technology of e-Health monitoring systems using Wireless Body Area Network (WBAN) that can collect patient's data. Since patient's data is private that makes securing the WBAN is essential. In this paper there is a proposed design architecture to secure data transmission from WBAN sensor to mobile in e-Health monitoring system by encrypting the vital signs of a patient using Lightweight Encryption Algorithm (LEA).

The use of data mining techniques to predict the ranking of E-government services

Abstract: The usage and improvement of information and communication technologies to enhance public sector services (e-Government) was recognized as an important task for the majority of governments in developed countries. Several countries are working hard to improve their e-Government ranking to support their sustainable development. This study employed several data mining techniques to build models that can adequately predict the e-Government ranks of 192 United Nation countries and identify the factors that affect those ranks. Our analysis and results show that the attributes the UN uses to rank countries are well conceptualized and, therefore, we were able to accurately predict the e-Government ranking of the countries involved using supervised learning (classification) and supervised learning (regression). The analysis also shows that e-Government and telecommunication infrastructure index, fixed telephone subscriptions, Internet usage, human capital, and online service index are the most important factors in e-Government ranking.

Formal specification, refinement, and implementation of path planning

Abstract: We investigate navigation algorithms, and specif­ically path planning, a fundamental function of autonomous robots. We formally address the issue of enhancing reliability of the widely-used A∗ path planning algorithm. In our step-wise refinement process, we capture successively more concrete specifications by transforming a high-level specification into an equivalent executable program. To elaborate an initial repre­sentation of the A∗ algorithm, we express it in an abstract and intuitive, yet formal, description. We use traditional mathematical concepts, such as sets, functions and predicate logic to capture this description. We then use the Z specification language to effect the transformation from the mathematical description into Z schemas, thus obtaining a formal specification. We use CZT to perform syntax and type checking and the Z/EVES tool to automatically prove some properties about the specification. Subsequently, we use the Z formal refinement theory to generate the implementation specification. This stage involves both data and operation refinement and is carried out in several basic sub-steps. A Java-based simulation prototype that mirrors the implementation specification is developed in order to demonstrate the applicability of our software development approach.

Watermarking for protected fingerprint authentication

Abstract: This paper presents a spatial biometric watermarking scheme for multimodal authentication system. This method embeds the face features (watermark) into the fingerprint image (cover) via a generated secret key to locate the pixels to be watermarked while preserving the fingerprint minutia points. The face features are extracted using Orthogonal Locality Preserving Projections technique. The proposed scheme has the advantage that in addition to fingerprint matching, the recovered watermark during the decoding can be used to establish the authenticity of the fingerprint and the user. The experimental results obtained using the ORL face database and FVC2002 DB2 fingerprint database have showed that the fingerprint-face based multimodal authentication system has good performance accuracy.

Continuous health monitoring using smartphones — A case-study for monitoring diabetic patients in UAE

Abstract: With diabetes patients doubling every year especially in the UAE there is a need to curb this epidemic and help those who are affected to live an active life. Continuous monitoring of health indicators ensures prompt medical attention and reduction in fatalities. The primary challenge to continuously monitor diabetes is that glucose level measurement requires invasive methods. Moreover, continuous monitoring must happen remotely and therefore would require computing and networking technologies that is seamless, real-time, high speed, and with large storage capacities. With the increasing penetration of smartphones, especially in the UAE, we propose a framework for continuous monitoring of diabetes on the smartphone platform. We also survey the state-of-the-art in continuous health monitoring.

Overview of fingerprinting methods for local text reuse detection

Abstract: We overview several local text reuse detection methods based on fingerprinting techniques. We first define the context of local text reuse and situate it within the general spectrum of information retrieval in order to pinpoint its particular applicability and challenges. After a brief description of the major text reuse detection approaches, we introduce the general principles of fingerprinting algorithms from an information retrieval perspective. Three classes of fingerprinting methods (overlap, non-overlap, and randomized) are surveyed. Specific algorithms, such as k-gram, winnowing, hailstorm, DCT and hash-breaking, are described. The performance and characteristics of these algorithms are summarized based on data from the literature.

Revolutionizing the healthcare of the future through nanomedicine: Opportunities and challenges

Abstract: Nanotechnology refers to the design, production and application of structures, devices or systems at the incredibly small scale of atoms and molecules-the "nanoscale". As a result, this technology has the potential to remarkably affect the development of the healthcare sector by revolutionizing both the diagnostic and therapeutic approach of diseases. In this paper, current advances in modern medicine are presented and discussed. Drug delivery, gene delivery, immune system support and health monitoring are demonstrated as few examples of the many applications that uses nanotechnology in disease diagnosis. In addition, the technology of bionanosensors is presented to highlight their ability to sense the biochemical and biophysical signals associated with diseases at the molecular or cellular levels. Further, nanoparticles are demonstrated as essential building blocks of nanotechnology in which various types of materials are presented and characterized. Finally, the challenges and future trends associated with this developing technology are illustrated.

User interactivity in eHealth applications: A novel taxonomy

Abstract: User interactivity is a generally desirable goal in eHealth software applications. Such interactions can occur in the form of personalized feedback, targeted alerts and virtual assistants. Previous research has shown that interactive features in eHealth applications tend to improve user engagement and retention. However, there are no frameworks that classify levels of user interactivity in eHealth. We propose a novel taxonomy that ranges from static (non-interactive) to collaborative (social media) to consultative (telemedicine). This taxonomy is a useful reference for developing and evaluating eHealth applications.

Social desirability bias in software piracy research: Evidence from pilot studies

Abstract: Social desirability bias (SDB) is the under-or over-reporting of behaviors by a respondent in order to appear more acceptable, or gain the approval of others. The presence of SDB in studies of software piracy behavior has been suspected for long. However, few studies have explicitly addressed this issue in detail. In the current article, results from a set of pilot studies are reported. These pilot studies compare software piracy behavior in experimental studies to responses of intentions to pirate in paper-based scenarios, under equivalent conditions. The comparisons provide valuable preliminary insights into the understanding of SDB in software piracy, and suggest the need to account for SDB research in software piracy studies.

Secure kNN queries over outsourced spatial data for location-based services

Abstract: Cloud computing allows data owners to outsource their databases, eliminating the need for costly storage and computational resources. The key is to maintain data confidentiality with respect to third-party service providers along with providing query results in real-time to authorized users. In this paper, a transformation and encryption approach is proposed for spatial databases, where the service provider executes queries and returns results to the users. First, the approach uses the space-filling Hilbert curve to map each spatial point in the multidimensional space to a one-dimensional space. Next, the order-preserving encryption technique is applied to the transformed spatial data. The user issues spatial kNN queries to the service provider based on the Hilbert values and then uses the encryption key to decrypt the query response returned. Experiments are conducted to show that this approach reduces the query communication cost between the authorized user and the service provider.

iCrowd — A framework for monitoring of identifiable crowd

Abstract: To manage large crowded events is a very challenging task nowadays. People are looking for solutions in which they can easily monitor the crowd, trace individuals, study formation and deformation patterns of the crowd. Millions of Muslims from around the world gather and perform Hajj in Makkah, Saudi Arabia in the 12th month of every lunar year. To monitor the crowd during Hajj is a great challenge. In this paper, we are proposing an identifiable crowd monitoring framework named iCrowd. This framework collect, identify, infer, analyze, store and retrieve the real-time location information of each of the pre-registered participants (pilgrims), and provides a digital view of crowd in near real-time. iCrowd framework is designed on a three-layer approach, device layer, middleware layer, and the application layer. We demonstrate our proposed framework with simulated data in the context of the event of Hajj.

Integration of heterogeneous data sources in smart grid based on summary schema model

Abstract: The modern infrastructure of electric grid known as smart grid is based on advanced communication and information technologies. The concept of data integration between heterogeneous data sources of smart grid reveals some challenges. The focus of this paper is on data integration as one of the major challenges in IT infrastructure of smart grid. In this paper, a semantic-based hierarchical integration model based on Summary Schema Model (SSM) has been proposed. The proposed model aims to optimize the cost of query in distributed heterogeneous databases. We represent how implementing a multidatabase system based on a Summary Schema Model would help to address and resolve data integration issues in IT infrastructure of smart grid. The analysis shows that the SSM-based integration model reduces the query response time compared to classic schema integration model.

Semantic enterprise service bus for cultural heritage

Abstract: The problem of data flooding is becoming more and more important, and it is necessary to find a way to access relevant information and to collect information and data from different data sources. In the field of cultural heritage, users need to be able to find and extract information from databases of specific contexts (paintings, inscriptions, churches, old coins, etc.). The problem is that each of these databases has a different data model. A project created to solve this problem is Europeana, which aims to bring together data from different providers (museums, libraries or other entities) in a single dataset. This paper aims to propose an architecture for a heterogeneous data sources system for the integration of structured/semi-structured data sources, enabling the information content to be more accessible and searchable for users. The data integration model proposed in this paper aims to exploit the method of "schema matching", using ontology-based data integration techniques by automating the integration process.

A reconfigurable cylindrical dielectric resonator antenna for WiMAX/WLAN applications

Abstract: The main objective of the present study is to achieve the reconfigurability of a cylindrical dielectric resonator antenna (CDRA). The CDRA is excited with two different modes; the HEMjjg mode is excited via an aperture etched on the ground under the center of the CDRA, where the TM 01δ mode is excited from an etched slot under the side of the CDRA, the reconflgurabilty is realized using two PIN diodes. Two different cases of PIN diode (D1-ON/D2-OFF and vice versa) are investigated and analyzed. The proposed cylindrical dielectric resonator antenna (CDRA) can provides two bands around 3.77 GHz and 5.5 GHz with a reflection coefficient below than −10dB which is appropriate for WiMAX and WLAN applications, respectively. The antenna gain is stable in the two bands 3.77GHz/5.5GHz with 3.8 dBi and 4.43dBi, respectively. The simulation is performed using two simulators; the CST Microwave Studio and the HFSS Ansoft package.

Candidate document retrieval for Arabic-based text reuse detection on the web

Abstract: Given an input document d, the problem of local text reuse detection is to detect from a given documents collection, all the possible reused passages between d and the other documents. Comparing the passages of document d with the passages of every other document in the collection is obviously infeasible especially with large collections such as the Web. Therefore, selecting a subset of the documents that potentially contains reused text with d becomes a major step in the detection problem. This paper describes a new efficient approach of query formulation to retrieve Arabic-based candidate source documents from the Web. We evaluated the work using a collection of documents especially constructed for this work. The experiments show that on average, 79.97% of the Web documents used in the reused cases were successfully retrieved.

Miniaturized rectangular dielectric resonator antenna for WCS standards

Abstract: In this communication, we propose a miniaturized rectangular dielectric resonator antenna (RDRA) for wireless communication services (WCS). The studied structure consists of a rectangular Dielectric resonator stacked on a thick layer of dielectric material that has very high permittivity. The numerical analysis was done by two different electromagnetic modeling software; Ansoft HFSS and CST. The obtained results are given in terms of the reflection coefficients and the radiation characteristics of the proposed antenna. The proposed antenna design operates around 2.314 GHz and provides an impedance bandwidth of 20 MHz.

Authentication enhancement techniques for BAC in 2G E-passport

Abstract: Electronic passport is one of the hottest research fields nowadays due to reported different attacks against various countries. Several attacks such as brute force attack, guessing machine readable zone's information are performed on Basic Access Control Protocol (BAC) due to its low entropy. This paper presents two proposed authentication enhancement techniques for seed key of BAC. The first proposed enhancement technique depends on a password provided by the citizen as input to the inspection system at the border during the verification process. The second proposed enhancement technique depends on extracting minutiae features from a scanned citizen's fingerprint to increase strength of seed key. Performance evaluation experiments for proposed enhancement techniques are conducted using MATLAB proving that the proposed techniques enhance authentication procedures of BAC and increase entropy of seed key with minimum additional delay. A facial recognition database and fingerprint recognition database are tested proving the strength of proposed techniques against cracking.

On detecting communities in social networks with interests

Abstract: Social networks have gained a lot of interest in recent literature due to the huge amount of data that can be extracted from them. With this ever growing data, emerged the need for techniques to handle it and analyze it. Several papers have proposed many techniques to analyze a given social network from several aspects. Communities are a crucial property in social networks and community detection is considered one of the most important problems in these networks. For this, many papers have devised algorithms for detecting communities. The issue with these algorithms is that they only take into consideration the relation (or distance) between the nodes for detecting communities. In this paper, a new algorithm is proposed to detect communities based on the interests of the nodes rather than their distances from each other. The paper carries out some experiments to test how well is the clustering algorithm in terms of the accuracy and the execution time.