Mathematics

Numerical simulation models of water flow in variably saturated soils are important tools in water resource management, assessment of water-related disasters and agriculture. Richards equation is one of the most used models for the fluid flow simulation into porous media. It is a partial differential equation whereby analytical solutions are only possible after applying a number of restrictive assumptions. Therefore, the derivation of efficient numerical schemes for its approximated solution has to be computed by discretization methods. We propose a numerical procedure considering a simplified linearization scheme that makes it adaptable to parallel computing. A comparison in computational performances with three other numerical procedures is detailed for a large computation, including the assessment of the landslide hazard in real areas. We demonstrate the efficiency of the proposed numerical procedure by comparing the results we obtained with a parallel code.

Before the Web era various software development methodologies have been proposed for the development of software applications for different domains. The main objectives of those methodologies were to meet user's requirements, find out means to suggest a systematic software development and reduce the maintenance cost of the developed software. On the emergence of the Web and to develop the web-based software systems, some existing methodologies have been extended. Also, new approaches (or informal methodologies) are introduced for the development of web-based systems because the development process for these systems is not considered as an extension of the classical software engineering, although both development processes for web-based systems and non web-based systems have the same basic objective which is software development. Of course, the development of the web-based systems needs a new kind of development methodologies which should meet and capture their unique and different requirements. Currently available software development methodologies are inappropriate and unsuitable to use for the development of web-based software systems, especially for the third generation web, called Semantic Web. In this paper, we present a brief review of the existing software development methodologies for the development of web-based systems. Some informal software development methodologies (or approaches) for the semantic web are also reviewed. Then, based on this analytical review, we propose a model for the development of semantic web systems. This model can be used as a benchmark to propose formal methodologies for the development of the semantic web systems. [

The Internet of Things (IoT) relies heavily on wireless communication devices that are able to discover and interact with other wireless devices in their vicinity. The communication flexibility coupled with software vulnerabilities in devices, due to low cost and short time-to-market, exposes them to a high risk of malware infiltration. Malware may infect a large number of network devices using device-to-device (D2D) communication resulting in the formation of a botnet, i.e., a network of infected devices controlled by a common malware. A botmaster may exploit it to launch a network-wide attack sabotaging infrastructure and facilities, or for malicious purposes such as collecting ransom. In this paper, we propose an analytical model to study the D2D propagation of malware in wireless IoT networks. Leveraging tools from dynamic population processes and point process theory, we capture malware infiltration and coordination process over a network topology. The analysis of mean-field equilibrium in the population is used to construct and solve an optimization problem for the network defender to prevent botnet formation by patching devices while causing minimum overhead to network operation. The developed analytical model serves as a basis for assisting the planning, design, and defense of such networks from a defender's standpoint.

In recent years, we have witnessed the dramatic increase in the volume of mobile SMS (Short Messaging Service) spam. The reason is that operators-owing to fierce market competition-have introduced packages that allow their customers to send unlimited SMS in less than $1 a month. It not only degrades the service of cellular operators but also compromises security and privacy of users. In this paper, we analyze SMS spam to identify novel features that distinguishes it from benign SMS (ham). The novelty of our approach is that we intercept the SMS at the access layer of a mobile phone-in hexadecimal format-and extract two features: (1) octet bigrams, and (2) frequency distribution of octets. Later, we provide these features to a number of evolutionary and non-evolutionary classifiers to identify the best classifier for our mobile spam filtering system. We evaluate the detection rate and false alarm rate of our system-using different classifiers-on a real world dataset. The results of our experiments show that sUpervised Classifier System (UCS), by operating on the the above-mentioned features' set, achieves more than 89% detection rate and 0% false alarm rate.

In recent years, we have witnessed the dramatic increase in the volume of mobile SMS (Short Messaging Service) spam. The reason is that operators-owing to fierce market competition-have introduced packages that allow their customers to send unlimited SMS in less than $1 a month. It not only degrades the service of cellular operators but also compromises security and privacy of users. In this paper, we analyze SMS spam to identify novel features that distinguishes it from benign SMS (ham). The novelty of our approach is that we intercept the SMS at the access layer of a mobile phone-in hexadecimal format-and extract two features: (1) octet bigrams, and (2) frequency distribution of octets. Later, we provide these features to a number of evolutionary and non-evolutionary classifiers to identify the best classifier for our mobile spam filtering system. We evaluate the detection rate and false alarm rate of our system-using different classifiers-on a real world dataset. The results of our experiments show that sUpervised Classifier System (UCS), by operating on the the above-mentioned features' set, achieves more than 89% detection rate and 0% false alarm rate.

Carrier sense multiple access (CSMA) protocol is standardized for vehicular communication to ensure a distributed and efficient communication between vehicles. However, several vehicular applications require efficient multi-hop information dissemination. This paper exploits stochastic geometry to develop a tractable and accurate modeling framework to characterize the multi-hop transmissions for vehicular networks in a multi-lane highway setup. In particular, we study the tradeoffs between per-hop packet forward progress, per-hop transmission success probability, and spatial frequency reuse (SFR) efficiency imposed by different packet forwarding schemes, namely, most forward with fixed radius (MFR), the nearest with forward progress (NFP), and the random with forward progress (RFP). We also define a new performance metric, denoted as the aggregate packet progress (APP), which is a dimensionless quantity that captures the aforementioned tradeoffs. To this end, the developed model reveals the interplay between the spectrum sensing threshold (ρ th) of the CSMA protocol and the packet forwarding scheme. Our results show that, in contrary to ALOHA networks which always favor NFP, MFR may achieve the highest APP in CSMA networks if ρ th is properly chosen.

This paper presents a methodology to quantify equivalent viscous damping in a turbine blade Material and friction dampings are included. The damping is quantified as a function of strain amplitude at a reference point in the blade for each mode at different frequencies.Damping is a phenomenon by which mechanical energy is dissipated, usually converted as a thermal energy in dynamic systems. The damping caused by friction between the internal planes that slip or slide as the material deforms is called hysteresis damping or material damping. This paper deals with determining hysteresis damping of a typical turbine blade. The damping is quantified as a function of strain amplitude.ANSYS and Hyper Mesh are adopted for necessary calculations. First the natural frequencies and orthonormal mode shapes are obtained at the desired speed. Lazan's damping law is used to determine the specific damping energy in each element of the blade. Total damping energy and strain energy are calculated by integrating them over the entire volume. With the help of these the loss factor is obtained. From the loss factor, the equivalent viscous damping ratio is determined.

In this paper, the production decisions across multiple energy suppliers in smart grid, powering cellular networks are investigated. The suppliers are characterized by different offered prices and pollutant emissions levels. The challenge is to decide the amount of energy provided by each supplier to each of the operators such that their profitability is maximized while respecting the maximum tolerated level of CO2 emissions. The cellular operators are characterized by their offered quality of service (QoS) to the subscribers and the number of users that determines their energy requirements. Stochastic geometry is used to determine the average power needed to achieve the target probability of coverage for each operator. The total average power requirements of all networks are fed to an optimization framework to find the optimal amount of energy to be provided from each supplier to the operators. The generalized alpha-fair utility function is used to avoid production bias among the s...

In this paper, the production decisions across multiple energy suppliers in smart grid, powering cellular networks are investigated. The suppliers are characterized by different offered prices and pollutant emissions levels. The challenge is to decide the amount of energy provided by each supplier to each of the operators such that their profitability is maximized while respecting the maximum tolerated level of CO2 emissions. The cellular operators are characterized by their offered quality of service (QoS) to the subscribers and the number of users that determines their energy requirements. Stochastic geometry is used to determine the average power needed to achieve the target probability of coverage for each operator. The total average power requirements of all networks are fed to an optimization framework to find the optimal amount of energy to be provided from each supplier to the operators. The generalized alphafair utility function is used to avoid production bias among the suppliers based on profitability of generation. Results illustrate the production behavior of the energy suppliers versus QoS level, cost of energy, capacity of generation, and level of fairness.

Red cell distribution width (RDW), expressed in femtoliters (fl), is a measure of the variation in the size of circulating erythrocytes and is often expressed as a direct measurement of the width of the distribution. We aim to observe the mean value of red cell distribution width (RDW) in hypertensive patients. Increased RDW can be used as a tool for early diagnosis, as an inflammatory marker, and a mortality indicator in hypertensive patients due to its close relation to inflammation. Materials and methodology Hypertensive patients who had the condition for more than one year duration, diagnosed according to the Joint National Committee (JNC 7) criteria were subjected to complete blood count and RDW measurement. One hundred patients, aged between 12 years and 65 years were enrolled from the outpatient department of medicine at the Military Hospital Rawalpindi. Results The mean age (± SD) of the patients was 51.48 ± 10.08 years. Out of 100 patients 69% were males whereas 31% were females. The overall frequency of hypertension more than five years was 55% subjects whereas 45% individuals had duration of hypertension less than five years. Mean RDW in females was found to be 49.35±8.42 fl while mean RDW in males was 44.78±7.11 fl. An independent sample t-test was applied to assess if there was any significant difference between age and gender. No significant difference between age and gender was found (p<0.05). The Mann-Whitney test was used to assess any association of RDW with gender. RDW values in females was found to be statistically significantly higher than in males (U=603, p=0.01). Linear regression showed that mean RDW value increased with increasing age (P <0.001). Conclusions A significant number of patients with hypertension have increased levels of RDW. Therefore, it is recommended that serum RDW should be checked regularly in patients with hypertension.

Cellular operators are increasingly turning towards renewable energy (RE) as an alternative to using traditional electricity in order to reduce operational expenditure and carbon footprint. Due to the randomness in both RE generation and mobile traffic at each base station (BS), a surplus or shortfall of energy may occur at any given time. To increase energy selfreliance and minimize the network's energy cost, the operator needs to efficiently exploit the RE generated across all BSs. In this paper, a hybrid energy sharing framework for cellular network is proposed, where a combination of physical power lines and energy trading with other BSs using smart grid is used. Algorithms for physical power lines deployment between BSs, based on average and complete statistics of the net RE available, are developed. Afterwards, an energy management framework is formulated to optimally determine the quantities of electricity and RE to be procured and exchanged among BSs, respectively, while considering battery capacities and real-time energy pricing. Three cases are investigated where RE generation is unknown, perfectly known, and partially known ahead of time. Results investigate the time varying energy management of BSs and demonstrate considerable reduction in average energy cost thanks to the hybrid energy sharing scheme.

In this paper, the problem of energy efficiency in cellular heterogeneous networks (HetNets) is investigated using radio resource and power management combined with the base station (BS) ON/OFF switching. The objective is to minimize the total power consumption of the network while satisfying the quality of service (QoS) requirements of each connected user. We consider the case of co-existing macrocell BS, small cell BSs, and private femtocell access points (FAPs). Three different network scenarios are investigated, depending on the status of the FAPs, i.e., HetNets without FAPs, HetNets with closed FAPs, and HetNets with semi-closed FAPs. A unified framework is proposed to simultaneously allocate spectrum resources to users in an energy efficient manner and switch off redundant small cell BSs. The high complexity dual decomposition technique is employed to achieve optimal solutions for the problem. A low complexity iterative algorithm is also proposed and its performances are compared to those of the optimal technique. The particularly interesting case of semi-closed FAPs, in which the FAPs accept to serve external users, achieves the highest energy efficiency due to increased degrees of freedom. In this paper, a cooperation scheme between FAPs and mobile operator is also investigated. The incentives for FAPs, e.g., renewable energy sharing and roaming prices, enabling cooperation are discussed to be considered as a useful guideline for inter-operator agreements. Index Terms-Base station ON/OFF switching, femtocell access points, green networking, heterogeneous networks. I. INTRODUCTION With the ever increasing number of mobile broadband data users and bandwidth-intensive services, the demand for radio resources has increased tremendously. One of the methods

This paper proposes and investigates a green virtualization framework for infrastructure sharing among multiple cellular operators whose networks are powered by a combination of conventional and renewable sources of energy. Under the proposed framework, the virtual network formed by unifying radio access infrastructures of all operators is optimized for minimum energy consumption by deactivating base stations (BSs) with low traffic loads. The users initially associated to those BSs are off-loaded to neighboring active ones. A fairness criterion for collaboration based on roaming prices is introduced to cover the additional energy costs incurred by host operators. The framework also ensures that any collaborating operator is not negatively affected by its participation in the proposed virtualization. A multi-objective linear programming problem is formulated to achieve energy and cost efficiency of the networks' operation by identifying the set of inter-operator roaming prices. For the case when collaboration among all operators is infeasible due to profitability, capacity, or power constraints, an iterative algorithm is proposed to determine the groups of operators that can viably collaborate. Results show significant energy savings using the proposed virtualization as compared to the standalone case. Moreover, collaborative operators exploiting locally generated renewable energy are rewarded more than traditional ones.

Enabling the Internet of things in remote environments without traditional communication infrastructure requires a multi-layer network architecture. Devices in the overlay network such as unmanned aerial vehicles (UAVs) are required to provide coverage to underlay devices as well as remain connected to other overlay devices to exploit device-to-device (D2D) communication. The coordination, planning, and design of such overlay networks constrained by the underlay devices is a challenging problem. Existing frameworks for placement of UAVs do not consider the lack of backhaul connectivity and the need for D2D communication. Furthermore, they ignore the dynamical aspects of connectivity in such networks which presents additional challenges. For instance, the connectivity of devices can be affected by changes in the network, e.g., the mobility of underlay devices or unavailability of overlay devices due to failure or adversarial attacks. To this end, this work proposes a feedback based adaptive, self-configurable, and resilient framework for the overlay network that cognitively adapts to the changes in the network to provide reliable connectivity between spatially dispersed smart devices. Results show that the proposed framework requires significantly lower number of aerial base stations to provide higher coverage and connectivity to remotely deployed mobile devices as compared to existing approaches. Index Terms-Connectivity, feedback, Internet of things, resilience, unmanned aerial vehicles. I. INTRODUCTION Connectivity between smart devices is vital in enabling the emerging paradigm of the Internet of things (IoT) [2]. The fundamental goal of the IoT is to interconnect smart objects so that they can exchange data and leverage the capabilities of each other to achieve individual and/or network objectives such as high situational awareness, efficiency, accuracy and revenue, etc. This connectivity relies on wireless communication networks which have their limitations based on the communication technologies involved. Existing IoT devices are connected to an access point using wireless personal area network (WPAN) technologies [3] such as WiFi, Bluetooth, Zigbee, etc. The access points are in-turn connected to the

The Internet of things (IoT) is revolutionizing the management and control of automated systems leading to a paradigm shift in areas such as smart homes, smart cities, health care, transportation, etc. The IoT technology is also envisioned to play an important role in improving the effectiveness of military operations in battlefields. The interconnection of combat equipment and other battlefield resources for coordinated automated decisions is referred to as the Internet of battlefield things (IoBT). IoBT networks are significantly different from traditional IoT networks due to battlefield specific challenges such as the absence of communication infrastructure, heterogeneity of devices, and susceptibility to cyber-physical attacks. The combat efficiency and coordinated decision-making in war scenarios depends highly on real-time data collection, which in turn relies on the connectivity of the network and information dissemination in the presence of adversaries. This work aims to build the theoretical foundations of designing secure and reconfigurable IoBT networks. Leveraging the theories of stochastic geometry and mathematical epidemiology, we develop an integrated framework to quantify the information dissemination among heterogeneous network devices. Consequently, a tractable optimization problem is formulated that can assist commanders in cost effectively planning the network and reconfiguring it according to the changing mission requirements. Index Terms-Battlefield, epidemics, internet of things, multiplex networks, Poisson point process, random geometric graph. Preliminary results have been presented at the 15th Intl. Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt 2017) [1].