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The multilevel inverter is a power electronic circuit that can give output voltage with multiple levels and be worked in inverter or rectifier mode. It is a highly efficient technique for DC to AC power conversion in solar photovoltaic systems due to its low total harmonic distortion (THD), low switching loss, low electromagnetic distortion for medium voltage and high-power applications. This paper describes a newly effective topology which has only eighteen switches, six voltage sources and six power diodes for three phase seven level inverter. For the controlling process of multilevel inverter different phase disposed carrier wave modulations are used. The aim is to thoroughly investigate and evaluate some optimum conditional points for these control techniques based on which proposed inverter will be more feasible and efficient. The effectiveness of the proposed system has been verified through simulation analysis in the MATLAB/Simulink software environment. From the simulation, it is observed that the proposed topology reduces the number of switches, voltage sources and power diodes among existing topologies. Based on the simulation result, it is also observed that the optimum modulation index and carrier frequency for PODSPWM are 1.10 and 1000Hz and for PODTRPWM are 1.10 and 1000Hz and for PODSDPWM are 1.0 and 1000Hz and also for PODTHPWM is 1.0 and 1000Hz and PODTRPWM offers better result in terms of THDs and PODSDPWM offers less switching losses among different topologies. The proposed asymmetric multilevel inverter offers less amount of switching devices. Besides, the efficiency of the inverter is increased due to minimum switching loss as well as reduced overall system installation cost.

This paper presents the development of a web-based tour package system. The objective of this paper is to present a review of a web-based system intended for the eco-tourism market in Bangladesh. This paper analyses and discusses the development cycle of the software and the tools used in the development cycle. The paper looks at the design impact of the application and attempts to identify the factors affected by the application. Using the developed web application, users can view and sign up for advertised tours and pay for the tour using a digital payment system. Each advertised tour contains information regarding the tour and users can view reviews written by previous travelers. Using the developed web application, users can view the location of a tourist spots and can get an idea about the distance between the user's current location and the tourist spots. There will be tour guides to guide the travelers to visit all the tourist spots under a tour package. This application will help the growth of the tourism industry by helping users with better accessibility to affordable options.

Cyber Emergency Response Team (CERT) is one of the very important component at the national level for the protection and monitoring of cyber domain across the country. As the digital contents are increasing in Bangladesh so is its vulnerability. CERT has been included in the National Cyber Security Strategy and Digital Security Act 2018 but its existence is only at the rudimentary stage with the absence of its footprint at the operational level. This study presents a framework of CERT for Bangladesh considering its application at operational level. The factors considered in this model are status of readiness for CERT, the parties involved in the response mechanism and the procedures involved. The proposed model will present an effective CERT in the domain of digitization and information sharing and will guide to a comprehensive approach to address any cyber incident. This would not only help taking effective measures to mitigate the effect of any cyber-attack but also to increase the cyber readiness profile of the nation to detect, prevent or minimize the occurrence of cyber incidents.

As the dependency on cyberspace increases, the developing nations find it increasingly difficult to combat cyber threats. This study suggests a holistic approach to face the aforementioned threats for a developing nation integrating both internal and external resources. This is a descriptive study based on online resources and various publications. The developing nations/states remain vulnerable to all forms of cyber threats purported by malicious individuals, organizations, and even by the state actors. In one hand, these smaller nations lack public awareness in using IT resources, on the other hand they cannot afford required advanced skill base, tools and infrastructures. Therefore, they need a holistic approach to thwart cyber threats emanating both from internal and external agents. Domestically, the developing countries can raise public awareness, develop required skill base, infrastructures, and form public-pri-vate partnerships. Internationally, respecting own national interests, the countries can form alliance to share tools and skills. It is expected that such efforts will help the developing countries to secure cyberspace from various forms of threats.

Image noise is a prevalent issue often created by inadequate lighting, cameras of low quality, compression of images and other factors. While low image quality is anticipated to degrade visual identification outcomes, most present object recognition techniques and benchmarks, such as Pascal Visual Object Classes Challenge and Microsoft Common Objects in Context Challenge, concentrate on images of comparatively high quality. Meanwhile, the identification of objects in noisy images in surveillance and other fields is a prevalent issue. In this paper we discuss the detection of objects in noisy images and suggest a new low-cost technique to detect image objects from noisy images. Receiving the benefits of the Single Shot MultiBox Detector (SSD), we have presented an extensive experimental assessment with conventional detectors retrained on noisy images. Results are provided for the prevalent benchmark for object detection Pascal Visual Object Classes. Comparing with other image detection approaches, our technique has provided satisfactory performance at the time of detecting image objects from noisy images. The method can be very effective to the autonomous industries to resolve the object detection related difficulties created by insufficient lighting and lower regulation pictures.

The overall goal of the research work is to localize user needs and discover ways to implement electronics into the inhaler in order to solve the needs and improve the user experience and service provisioning. Planning a context-aware middleware may be a challenging issue because of particular characteristics of settings and gadgets such as the energetic nature of setting and asset confinement of gadgets. Moreover, the middleware ought to give an agreeable framework in which application designers seem effortlessly trade determining relevant data. To address these issues, a structural plan of a smart-inhaler for context-aware middleware is proposed in this paper that bolsters participation among application engineers. Our whole system is IoT based and our output will give an efficient system for the patients of Asthma. In this work, different types of sensors and the connections between the sensors and server are the main base of the system. Different types of sensors have been used for the working process and for the base system SOC (system on chip). Most importantly, this system should provide a good connection with the smartphone. As asthma patients consider inhaler to be their lifesaver, it needs to be efficient and user friendly. Considering all the possible options we have tried to deliver a smart product to those asthma patients.

The aim of this project is to analyze and predict the quality of river water for daily usage and agricultural purpose. Water is one of the most essential elements of nature that contributes to perform biological operations of all living bodies on earth. The quality of water impacts directly on living bodies. Change in water quality causes great damage to the living species. Through this project we have schemed to detect the alteration earlier so that crucial steps can be undertaken to prevent impending losses. Taking advantage to the Gradient Boosting Model (GBM), the water quality was examined and forecasted. With the help of automatic water parameter measuring tools, samples were collected from numerous rivers of Bangladesh. The GBM was instructed utilizing the samples collected from year 2013 to 2019. The model functions using specified arguments. The model evaluates the water quality and anticipates the change that demonstrates the future water quality. The findings suggest that the model's expected values and actual values are in excellent agreement and the future change in water quality has been reported correctly.

The application of Internet of Things (IoT) in a poultry farm allows a real-time monitoring of the context of the farm through notification to smartphone, predicts the context in advance, advises right decision at the right time that saves poultry lives, minimize the economic loss, and improves the productivity and quality. Monitoring weather of the poultry farm is one of the important issues that involves monitoring the status of the temperature, humidity, etc. that has impact on raw materials and quality of food, health condition of the poultry, feeding in time, food management, etc. Considering the fact, to improve the management and to increase the efficiency of the farm, an IoT based weather monitoring system for a poultry farm has been proposed in this article. DHT11 is used to measure the temperature and humidity in the proposed system. The collected data is transmitted to a cloud-based server, stored in a database and compared with threshold values continuously. If the stream of data crosses the threshold values and remains higher for certain duration than the system sends an alert message to smartphone and a signal to a buzzer. To validate, the proposed system has been implemented that sends alert messages to smartphone and signals to a buzzer successfully.

This paper represents an IoT based tracking system, through which it is very easy to track the child, elder, or any type of luggage. This system has separate features for tracking each of these things, which have been completed by the IoT device and the Android app. It is possible to track anything manually or automatically with this device. NodeMCU, GPS, and GSM have been used as hardware to build the system, and Firebase Server and Google API services have been used for the Android app. Parcel exchange has become very common nowadays. With this system, in addition, the location of the parcel can be easily tracked, and administrative help can be taken for any unforeseen situation.

The paper depicts the in-depth review of laser surface texturing on engineering materials considering its application in the field of biomedical applications. A sufficient literature survey has been done and the important aspects have been critically reviewed. The effect of laser surface texturing on various parameters of the biomedical application has been reviewed and presented in the concise form. The review suggested that laser surface texturing has a significant influence on the engineering materials in terms of biomedical application.

Data-driven approaches, e.g., deep learning (DL),have been widely studied in terrestrial wireless communications fields, proving the benefits and potentials of such techniques. In comparison, DL for satellite networks is studied to a limited extent in the literature. In this paper, we develop a DL assisted approach to facilitate efficient beam hopping (BH) in multibeam satellite systems. BH is adopted to provide a high level of flexibility to manage irregular and time variant traffic requests in the satellite coverage area. Conventional iterative optimization approaches and typical data-driven techniques may have their respective limitations in achieving timely and satisfactory performance. We herein explore a combined learning-and-optimization approach to provide a fast, feasible, and near-optimal solution for BH scheduling. Numerical study shows that in the proposed solution, the learning component is able to largely accelerate the procedure of BH pattern selection and allocation, while the optimization component can guarantee the solution’s feasibility and improve the overall performance.

Carrier Aggregation (CA) is an integral part of current terrestrial networks. Its ability to enhance the peak data rate, to efficiently utilize the limited available spectrum resources and to satisfy the demand for data-hungry applications has drawn large attention from different wireless network communities. Given the benefits of CA in the terrestrial wireless environment, it is of great interest to analyze and evaluate the potential impact of CA in the satellite domain. In this paper, we study CA in multi-beam high throughput satellite systems. We consider both inter-transponder and intra-transponder CA at the satellite payload level of the communication stack, and we address the problem of carrier-user assignment assuming that multiple users can be multiplexed in each carrier. The transmission parameters of different carriers are generated considering the transmission characteristics of carriers in different transponders. In particular, we propose a flexible carrier allocation approach for a CA enabled multi-beam satellite system targeting a proportionally fair user demand satisfaction. Simulation results and analysis shed some light on this rather unexplored scenario and demonstrate the feasibility of the CA in satellite communication systems.

This paper designs dynamic onboard signal processing schemes in a multiple gateway multi-beam satellite system where full frequency reuse pattern is considered among the beams and feeds. In particular, we deploy on-board Joint Precoding, Feed selection and Signal switching mechanism (JPFS) so that the following advantages are realized, I) No need of Channel State Information (CSI) exchange among the gateways and satellite, since the performance of precoding is highly sensitive to the quality of CSI, II) In case one gateway fails, rerouting signals through other gateways can be applied without any extra signal processing, III) Properly selecting on-board feed/s to serve each user which generates maximum gain toward corresponding user, IV) Flexibly switching the signals received from the gateways to requested users where each user can dynamically request traffic from any gateway, and V) Multiple users with multiple traffic streams can be dynamically served at each beam. However, deploying such JPFS architecture imposes high complexity to the satellite payload. To tackle this issue, this study aims at deploying JPFS that can provide affordable complexity at the payload. In addition, while increasing the data demand imposes extensive bandwidth resources requirement in the feeder link, the proposed JPFS design works efficiently with available feeder link resources even if the data demand increases. The proposed design is evaluated with a close-to-real beam pattern and the latest broadband communication standard for satellite communications.

Multi criteria optimization of WEDM of D3 die steel is presented in this paper where machining is done with brass wire as electrode. Four input process parameters such as pulse off time, servo voltage, and pulse on time and wire tension were considered during operation. The experiment was conducted and the output variables like cutting speed and surface roughness are evaluated at various parametric combination. Taguchi L16 orthogonal array experimental design was utilized and the result was optimized using MABAC method for minimizing surface roughness value and maximizing cutting speed.

Multipath TCP (MPTCP) has been increasingly adopted in the current and next generation of mobile wireless networks. MPTCP can exploit multiple wireless links for an application; hence it enhances not only the reliability but also the performance of TCP in the same scenario. However, most of the state-of-the-art congestion controls for MPTCP share the same behavior of TCP when a lost packet happens on a path. Therefore, MPTCP also incurs performance degradation when the number of lost packets increases (i.e., the well-known problem of TCP). Comparing to TCP, the deterioration in MPTCP maybe even worse, especially when the loss simultaneously happens on multiple paths. Since the lossy paths likely occur in wireless networks, the improvement of MPTCP in such environment is necessary. In this work, we explore the feasibility of applying a novel approach of handling loss in TCP congestion control to MPTCP. Specifically, we investigate and extend the bottleneck bandwidth round trip time (BBR) algorithm, which reacts to the loss signal in TCP following an estimation model, for MPTCP. We integrate BBR to MPTCP in a new implementation, namely mpbbr. We then evaluation mpbbr under the lossy networks in comparison to the MPTCP with the balia congestion control. The evaluation results show that mpbbr well handles against the lossy conditions as well as outperforms balia in the investigated scenarios.

The 3rd generation partnership project (3GPP) has recently specified the non-standalone 5G New Radio (NR), in which the dual connectivity (DC) feature plays an essential role. A User Equipment (UE) with DC is able to concurrently connect to an evolved NodeB (eNB) (e.g., using LTE in a macro cell) and a next generation NodeB (gNB) (e.g., using 5G NR in a small cell) aiming to satisfy the 5G's required Key Performance Indicators (KPIs). In this work, we focus on the issue of concurrent transmissions on the 5G small cell, which potentially exploit the benefits of DC. With DC, an application is able to spread its traffic over different two paths (via eNB and gNB) between the UE and the LTE core network. The traffic over diverse paths may experience different delay since the conditions are generally different (e.g., due to wireless channel, background traffic). Therefore, one of the most important problems in efficient operation with DC is minimizing the end-to-end delay considering all the connections. To address that problem, we adopt the deterministic network calculus to first characterize the delay experienced by each connection; then to model the overall end-to- end delay in the 5G small cell. We then formulate an optimization problem that attempts to find the optimal traffic splitting over the connections while minimizing the delay. We derive the solution for the problem, as well as, present the numerical results.

The shared resource access wireless communication system is regarded as a paradigm that allows the mobile network operators (MNOs) to have extended coverage and allows them to satisfy their subscribers' high capacity demands while keeping the capital and operational expenditure in check. On the other hand, dual connectivity (DC), a small cell enhancement feature, allows the subscribers to have two simultaneous connections increasing throughput and enhancing mobility robustness. For the DC mechanism, the user needs to be under the coverage of multiple BSs concurrently. Because of random nature of the wireless links and distribution of BSs in a network, the practicability/operability of DC for a typical user under such random operating conditions (both topological and wireless link randomness) needs to be properly evaluated. In this paper, we perform stochastic analysis of DC in shared resource access high capacity wireless networks. We consider a fading-averaged signal propagation loss process, where the selection of the serving BS is perturbed shadowing, not by fading. The DC coverage probability is analyzed in terms of tractable, integral expressions. We have observed that the DC coverage probability is greatly affected by the density of the small cell BSs and the variance of the log-normal shadowing.

The small cell network is one of the emerging technologies for the next generation wireless systems. It can enlarge cell coverage, boost peak data rate, improve link quality, and offer flexible deployment. In this paper, we investigate a specific small cell network scenario, where the density of small cell base stations (BS) is much higher than that of user equipments (UE). Under this condition, each UE can be served by multiple small cell BSs, which also motivates the use of coordinated multi-point (CoMP) transmissions in dense small cell networks. Therefore, in this paper, we investigate the small cell network with highly dense deployment of small cell BSs, and propose CoMP set formulation method, which selects small cell BSs according to the designed metric, for downlink (DL) transmissions. We also conduct simulations to validate the performance of the proposed method, and the simulation results show that the proposed CoMP method can indeed improve the performance of dense small cell networks and hence offer better communication quality.

Data interoperability is a prerequisite to achieve cross-community and cross-application sharing of information and knowledge. Heterogeneous data from multiple sources including semantic and non-semantic data sources (e.g. SNS data, web data, relational data, RDF, XML, CSV, etc.) have an important effect for IoT service provisioning. The data are not in a same type or format always that requires to be processed and transformed into a machine readable semantic format so that systems can understand each other to create and offer services. This paper proposes a framework that considers both semantic and non-semantic data sources to process them for data interoperability in Web Objects enabled IoT environment. WoO is a service platform that provides a resourceful infrastructure to deploy IoT services in the World Wide Web environment. For data interoperability, heterogeneous data are transformed following a semantic data schema that has been defined using a standard schema. The heterogeneous data are processed and stored in a knowledge base in RDF/OWL format.

To make WiGig/IEEE 802.11ad backward compatible with the legacy Wi-Fi, a multi-band device that is capable of WiGig and Wi-Fi is necessarily equipped a function of fast switchover between the WiGig and Wi-Fi link. It is expected that the switching action is done as quickly as possible in order to minimize negative effects on an ongoing application. The IEEE 802.11ad standard defines the switching operation within the scope of fast session transfer (FST) protocol. To properly run FST, the device needs extra layer-2 entities that simultaneously manage the PHY/MAC states of multiple radios. Although introducing WiGig radios is a trivial task, installing those entities on an existing legacy Wi-Fi network is unfortunately a challenging one. This work presents an experimental feasibility study of achieving the backward compatibility without FST. We initially analyze the feasible capability of multipath transmission control protocol (MPTCP). We then setup a real- world testbed and evaluate different operational modes of MPTCP, aiming to find the most suitable one. Our experimental results show that the fast switchover between a multi-Gigabit WiGig and a legacy Wi-Fi link is achievable with the MPTCP's backup mode.

Reducing energy consumption while satisfying user living comfort is a challenging issue in IoT environment for utilities and service providers. Energy consumption needs to be reduced without compromising user comfort that depends not only on current environment condition but also real world knowledge, history data and user preferences. Web Objects based IoT environment allows objects virtualization and use of semantic ontology to create real world knowledge and applies cognitive functionalities to learn user preferences. Web Objects based IoT environment allows integration of connected objects and isolation of information from multiple application domains. Depending on user current situation, location, time, history data and future prediction, energy efficiency on WoO make intelligent decision to offer services for user comfort living and reduce energy consumption. This paper proposes an architecture that supports Web Objects based energy efficiency for smart home IoT services. To realize knowledge-based intelligent IoT services, a use case scenario has been studied.

The vision of internet of things is to connect every object beyond the boundaries of anywhere and whenever for the provision of services from the smart home user to fourth industrial revolution. The objects in the internet of things will be more heterogeneous because of their specialty and accuracy in their domain. Now a days in the Internet of things the data and its machine understanding gets more importance and remain the focal point rather than the objects that generate that data changes frequently due to innovations and their wears and tears. To make the machine understanding, exchanging and sharing information and knowledge; these objects needs a light weight and novel platform for the provision of IoT services in the future. The Web of Objects is a platform for IoT services because of its service modularity with the support of interoperable microservices and virtualization and granularity of heterogeneous objects through composite virtual objects and virtual objects. To realize the cross domain IoT applications we proposed WoO enabled interoperable microservices architecture and present a reference use case for the implementation.

In ubiquitous IoT environment, recommending services are getting popular in daily livings that depend on user identification, location, activity, situation and preferences. To provide scalable and dynamic solutions for smart spaces service features, Web of Objects facilitates real world object virtualization using semantic ontology. Cognitive functionalities in Web of Objects combines intelligence and analytics to create knowledge-based services and hence results in better service provisioning. This paper discusses the functional architecture of three levels on Web of Objects platform. Finally, a use case scenario for smart spaces has been studied.

The IEEE 802.11ad standard allows wireless devices to operate in the unlicensed spectrum band of 60 GHz. By utilizing the channel with 2.16 GHz width, the devices are able to transmit at multi-Gigabit data rates that potentially satisfy demanding requirements of quality of services. Additionally, the advent of off-the-shelf IEEE 802.11ad device motivates research efforts to exploit this 60 GHz opportunity for applications. Although much has been understood from the previous works, there is still a lack of insight into building IEEE 802.11ad networks, especially the ones with multi-Gigabit links. Address the issue, this work investigates the feasibility of multi-Gigabit IEEE 802.11ad networks, as well as, the factors that influence network performance in a typical office environment. By experimental study with off-the-shelf IEEE 802.11ad hardware, we can identify the conditions that the TCP and UDP throughput of IEEE 802.11ad link reach multi-Gigabit levels. Moreover, we show and discuss the negative effects of both co-channel and adjacent channel interference on the IEEE 802.11ad network's performance.

One of the reasons behind failure or not being successful of an IoT service is due to the fact that, such a service do not cater to the end user needs precisely. An important ingredient in successful IoT service provisioning is to intelligently select service using the preferences and situation of requesting users. This not only provides effective service delivery but also reduces the time of service processing. Preferences of service user can be modeled by detecting regularities in their behavior and produce a hypothesis about their preferences. To enable service provisioning real world objects are virtualized using semantic ontology in Web of Objects (WoO) platform, to be interoperable and interconnected with each other. This paper proposes an approach to dynamic service provisioning based on user preferences and situation in a WoO enabled IoT system. It also contributes Real World Knowledge (RWK) model incorporating user preferences and situational information.

Multipath TCP (MPTCP) is an evolvable technology for bandwidth aggregation on a mobile device. MPTCP naturally and concurrently exploits wireless links via different interfaces (i.e., Wi-Fi and cellular) for data transferring. Theoretically, the MPTCP's aggregated throughput is better or at least equals to the TCP throughput over a link. However, our investigation of MPTCP performance in a lossy wireless environment shows that the theoretical statement does not always hold. Specifically, the aggregation benefit of MPTCP (i.e., in a comparison to TCP) becomes negative when the loss over a link surpasses specific levels. In this paper, we focus on finding the negative region of MPTCP's aggregation benefit by experimental study. Additionally, we propose a loss-aware disabling mechanism to bypass the negativity. The mechanism temporarily switches a wireless link to a backup mode when an observed loss value reaches a threshold. We integrate the mechanism with a state-of-the-art MPTCP implementation and compare the two MPTCPs in various lossy conditions. The evaluation results confirm the effectiveness of the newly proposed mechanism in terms of enhancing goodput and saving resources.

In a ubiquitous environment, due to continuous change of location of objects, tracking a moving object is a challenging task in intelligent IoT service provisioning. Hence, web-based IoT services can be provided by discovering and allocating only those virtual objects that are directly relevant to current location of the moving object. A semantic ontology is used to virtualize real world objects for interconnection and interoperability among virtual objects in multiple domains. Allocating relevant virtual objects requires prediction of next location of the objects through applying machine learning algorithm. Analyzing service request, prediction and real world knowledge, service request parameters are adjusted to discover relevant virtual objects dynamically as stream-variable dependency. This paper proposes an architecture that supports discovering and allocating relevant virtual objects based on context-awareness to track moving objects.

Small cell deployments are one of the most significant long-term strategic policies of the mobile network operators since small cell architecture delivers not only the required capacity boost but also the flexibility important for immensely-localized deployments in high-traffic environments. In HetNets, small cells serve as offloading spots in the radio access network to offload users and their associated traffic from congested macrocells. In this paper, we perform analytical analysis and investigate how the radio propagation effects such as multipath and shadowing, and small cell base station density affect macro users' offloading to small cell networks. In particular, we exploit composite fading channel in our evaluation when a macro user is offloaded to small cells networks within the stochastic heterogeneous networks framework. We derive the expressions for outage probability (equivalently success probability) of the macro user in macro network and small cells network for Nakagami-lognormal desired and interfering signals. We propose efficient approximation for the probability density functions of the channel fading power for shadowed Nakagami-m fading distribution that does not have closed-form expression employing Gauss-Hermite quadrature. Finally, the outage probability performance of macro user with and without offloading options/services is analyzed for various settings of fading channels.

Intelligent service provisioning for smart ageing requires not only the current status of smart objects, but also the knowledge of the service and its surrounding environment. Hence, context information is detected by processing the stream of data and the situation is recognized by reasoning them to project the prediction of the service environment as well as to update the knowledge. Knowledge based IoT service provisioning can be achieved in terms of virtual objects and composite virtual objects in the Web-of-Objects platform. Web-of-Objects allows the semantic ontology to virtualize the objects, which can express the knowledge through the interrelation of the virtual objects. This paper proposes a knowledge creation model in Web-of-Objects platform that helps in learning the status of the objects to update the knowledge through machine learning technique, which has been considered in service request analysis for user-centric service provisioning. To realize the intelligent service features, a use case scenario has been studied and a prototype has been implemented.

We consider the resource allocation (RA) optimization problem in shared spectrum access communications system, and propose efficient solutions for both inter-operator and intra-operator RA optimization problems. For inter-operator RA optimization, we present a spectrum sharing framework that primarily focuses on fairness issues for the spectrum sharing operators, by taking care of the sharing policy measures. For intra-operator RA, a joint subcarrier and power allocation scheme is considered for throughput maximization of a spectrum sharing operator employing exclusive assignment of subcarriers to its users under transmitting power constraint. Since the optimization problem is combinatorial with nonlinear constraints and has non-convex feasible regions, it is numerically very difficult to solve. We propose an efficient solution by linearizing and/or linearly approximating the nonlinear constraints, and by applying a transformation to a second order cone program form to handle the nonlinear objective function. The simulation results demonstrate the efficiency of the proposed solutions.

Intelligent service provisioning in the Internet of Things infrastructure can be achieved by discovering and composing most relevant virtual objects and autonomic modification of context information that require learning the system behavior through steady association between the virtual object and the real world object. To meet these challenges, Web-of-Objects enables the objects to be deployed, maintained and operated in the Internet of Things through virtualizing the real world objects with the use of semantic ontology. Learning model can be represented in terms of composite virtual object that is formed by combining multiple functionalities of virtual objects. Different functionalities at the virtual object level and their iteration enable the cognition in virtual object. The creation and functional architecture of virtual object in Web-of-Objects have been discussed. For the efficient discovery and composition of virtual object, a Web-of-Objects based learning model has been proposed in this paper. Finally, to realize the service composition, a use-case scenario has been studied.

This paper studies the resource allocation optimization problem under user rate constraints in a single cell multiuser orthogonal frequency division multiplexing system. Since the optimization problem does not have a convexity structure, it is numerically very difficult to solve and the optimal solution is computationally very expensive. We propose two efficient suboptimal solutions, i) based on Lagrange dual decomposition (LDD), and ii) based on separating the subcarrier and power allocation. The former solution employs subgradient method to optimize the dual variables. When the number of subcarriers is very large, it is shown that the solution obtained from LDD is optimal. However, because of non-convexity of the original optimization problem, the optimality is not guaranteed. The latter approach disjoints the subcarrier and power allocation. The subcarrier allocation is performed based on proportional data rate requirements, and finally optimal power allocation is performed under given subcarrier allocation. For both of the solutions, the achieved objective values are very close to the optimal solution, and have lower computational complexity.

We optimize the throughput of a single cell multiuser orthogonal frequency division multiplexing system with proportional data rate fairness requirements. The concept is to support mobile users with different levels of service. The optimization problem is a mixed binary integer nonlinear programming (MINLP) problem, which is computationally very expensive. We propose a computationally efficient near-optimal solution. The original MINLP problem is broken down to two subproblems by introducing auxiliary optimization variables and employing integer relaxation. A stochastic multi-start approach is invoked to facilitate escape from possible local minima. The simulation results show that the proposed solution exhibits very strong adherence to the desired proportional data rate fairness while achieving higher system throughput compared to the other existing solutions.

Context-awareness plays an important role to offer an intelligence in terms of provision of user-centric features in Internet of Things (IoT). Web of Objects (WoO) has been introduced to support a framework to simplify application deployment, maintenance and operation of IoT service infrastructure by classifying and integrating objects on the World Wide Web. The semantic ontology is applied on a WoO platform to virtualize the physical objects and information, which expresses knowledge that provides intelligence to the user-centric service. The user-centric service is realized in terms of composite virtual object that can be formed by combining functionalities of multiple virtual objects and service rules. Context-aware service features can be provided in terms of self-awareness that helps in achieving autonomous behavior of the system. The paper proposes a WoO based context-aware architecture. To realize the context-aware user-centric service features, a conceptual semantic ontology model and a knowledge creation model have been discussed.

Semantic ontology in Web of Object (WoO) creates and provides services in terms of Virtual Objects (VO) and Composite Virtual Object (CVO). Virtualizing the physical devices and resources as well as conceptual entities would form VOs, where CVOs are formed with the interrelated VOs to provide detailed information and services. Interaction between the physical devices and the smartphone on the physical web standard extends IoT services on WoO platform. Procedural approach for the interaction among the physical device, smartphone and WoO application server has been presented. A conceptual semantic ontology model for information reusability and interoperability among the VOs, the functional model of WoO platform and an implementation architecture have been presented.

Recently nanomaterial have gained a great interest due to their unique electrical and optical properties. The area of carbon materials have since been dominated by studies of carbon nanotubes. So far numerous methods have been developed for the synthesis of CNTs; in this work we have synthesized CNTs via a simple chemical route. Carbon nanotubes (CNTs) are successfully synthesized by heating a mixture of ferrocene and ammonium chloride at temperature as low as 250 °C. Carbon nanospheres are also observed here. Carbon spheres (CSs) of different sizes and shapes are present randomly in the sample. Field emission scanning electron microscopy is performed to examine the morphology of the sample and Energy Dispersive X-ray Spectroscopy (EDX) is performed to examine the composition.

This paper considers distributed linear beamforming in downlink multicell multiuser orthogonal frequency-division multiple access networks. A fast convergent solution maximizing the weighted sum- rate with per base station (BS) transmiting power constraint is formulated. We approximate the non- convex weighted sum-rate maximization (WSRM) problem with a semidefinite relaxed solvable convex form by means of a series of approximation based on interference alignment (IA) analysis. The WSRM optimization is a two-stage optimization process. In the first stage, the IA conditions are satisfied. In the second stage, the convex approximation of the non-convex WSRM is obtained based on the consequences of IA, and high signal-to-interference-plus-noise ratio assumption. Compared to the conventional iterative distributed algorithms where the BSs exchange additional information at each iteration, the BSs of our proposed solution optimize their beamformers locally without reporting additional information during the iterative procedure.

A theoretical study of optimized crystal structure with electronic, optical and elastic properties of newly synthesized Y 8 CoIn 3 is performed by using the first-principles pseudo-potential plane-wave method within the Generalized Gradient Approximation (GGA) in the scheme of Perdew-Burke-Ernzerhof (PBE). It is found that mainly 3d electrons of Yttrium (Y) and Cobalt (Co) contribute to DOS, which can influence the conduction phenomenon. The indirect band gap of this compound is found to be 0.034 eV. The optical properties such as dielectric function, refractive index, absorption coefficient and conductivity are calculated and explained. Based on the calculation of stress tensor it is found that Y 8 CoIn 3 possesses anisotropic elastic property. Mechanical properties such as bulk and shear modulus, Young's modulus, Poisson's ratio for Y 8 CoIn 3 , in the frame work of Voigt-Reuss-Hill, are also calculated. Furthermore, Debye temperature and transverse and longitudinal sound velocities were calculated by using obtained elastic constants.

Right skewed data is available in the field of health science, biological science, epidemiological science and others. This paper assessed some existing procedures for testing the difference of means of two right skewed populations. A Monte Carlo simulation study has been conducted to compare the performance of the test statistics in the sense of empirical size and power of the selected tests. Based on the simulation study results, some good test statistics are recommended for practitioners. A real life health related example has been considered to illustrate the application of the techniques.