The conventional mental healthcare regime follows a reactive, symptom-focused, and episodic approach in a non-continuous manner, wherein the individual discretely records their biomarker levels or vital signs for a short period prior to a subsequent doctor’s visit. Recognizing that each individual is unique and requires continuous stress monitoring and personally tailored treatment, we propose a holistic hybrid edge-cloud Wearable Internet of Things (WIoT)-based online stress monitoring solution to address the above needs. To eliminate the latency associated with cloud access, appropriate edge models—Spiking Neural Network (SNN), Conditionally Parameterized Convolutions (CondConv), and Support Vector Machine (SVM)—are trained, enabling low-energy real-time stress assessment near the subjects on the spot. This work leverages design-space exploration for the purpose of optimizing the performance and energy efficiency of machine learning inference at the edge. The cloud exploits a novel multimodal matching network model that outperforms six state-of-the-art stress recognition algorithms by 2-7% in terms of accuracy. An offloading decision process is formulated to strike the right balance between accuracy, latency, and energy. By addressing the interplay of edge-cloud, the proposed hierarchical solution leads to a reduction of 77.89% in response time and 78.56% in energy consumption with only a 7.6% drop in accuracy compared to the IoT-Cloud scheme, and it achieves a 5.8% increase in accuracy on average compared to the IoT-Edge scheme.

Fusing a low spatial resolution hyperspectral image (HSI) with a high spatial resolution multispectral image (MSI) to produce a fused high spatio-spectal resolution one, referred to as HSI super-resolution, has recently attracted increasing research interests. In this paper, a new method based on coupled non-negative tensor decomposition (CNTD) is proposed. The proposed method uses tucker tensor factorization for low resolution hyperspectral image (LR-HSI) and high resolution multispectral image (HR-MSI) under the constraint of non-negative tensor ecomposition (NTD). The conventional non-negative matrix factorization (NMF) method essentially loses spatio-spectral joint structure information when stacking a 3D data into a matrix form. On the contrary, in NMF-based methods, the spectral, spatial, or their joint structures must be imposed from outside as a constraint to well pose the NMF problem, The proposed CNTD method blindly brings the advantage of preserving the spatio-spectral joint structure of HSIs. In this paper, the NTD is imposed on the coupled tensor of HIS and MSI straightly. Hence the intrinsic spatio-spectral joint structure of HSI can be losslessly expressed and interdependently exploited. Furthermore, multilinear interactions of different modes of the HSIs can be exactly modeled by means of the core tensor of the Tucker tensor decomposition. The proposed method is completely straight forward and easy to implement. Unlike the other state-of-the-art methods, the complexity of the proposed CNTD method is quite linear with the size of the HSI cube. Compared with the state-of-the-art methods experiments on two well-known datasets, give promising results with lower complexity order.

Resource discovery is an important fundamental aspect and a crucial task in Mobile Peer-to-Peer Networks (MP2P). To compliment network dynamics and churn, the unstructured search architecture is widely used. The key goal of an efficient search scheme is to find the required resource with minimal search latency, low overhead, and low power consumption to better suit the nature of mobile nodes where resource constraints are the major bottleneck. Resource discovery thus becomes an integral part of the distributed architecture and resource sharing systems. In the past, many resource discovery strategies are proposed for Mobile P2P networks. A schematic and tabular classification of these systems enables one to review the existing works under one umbrella. This article presents an overview of such several different schemes for performing resource discovery in the MP2P network broadly classified under six different categories, i.e., centralized, unstructured, structured, super node based, hybrid, and other general lookup schemes. We also give a brief comparison of P2P, MANET, and P2P MANETs. Further, we discuss various routing schemes in such an evolving network. In this survey, we study and review the existing resource discovery techniques in MP2P systems. The classification of each scheme with their advantages and disadvantages are discussed. We highlight a few open research issues, and brief the role of network topology and its structure on the performance of the resource search protocols. Further, we also glimpse on the security threats in MP2P networks and suggest their countermeasures. And, finally, a summary of each method is given, along with their lookup complexities.

The use of deep learning for human identification and object detection is becoming ever more prevalent in the surveillance industry. These systems have been trained to identify human body's or faces with a high degree of accuracy. However, there have been successful attempts to fool these systems with different techniques called adversarial attacks. This paper presents an adversarial attack using infrared light on facial recognition systems. The relevance of this research is to exploit the physical downfalls of deep neural networks. This demonstration of weakness within these systems are in hopes that this research will be used in the future to improve the training models for object recognition. A research outline on infrared light and facial recognition are presented within this paper. A detailed analyzation of the current design phase and future steps of the of the project are presented including initial testing of the device. Any challenges are explored and evaluated such that the deliverables of the project remain consistent to its timeline. The project specifications may be subject to change overtime based on the outcomes of testing stages.

This work was presented at the 9th Joint Symposium on Computational Intelligence (JSCI9), organized by the IEEE-CIS Thailand Chapter, that aims to support research students and young researchers, to create a place enabling participants to share and discuss on their research prior to publishing their works. The event was open to all researchers who want to broaden their knowledge in the field of computational intelligence.

Automatic repeat request (ARQ) schemes, and in particular hybrid-ARQ (HARQ) schemes, which jointly adopt forward error correction (FEC) and ARQ, are essential to provide reliable data transmission in wireless communications systems. However, the feedback from the receiver to the transmitter and the retransmission process used in ARQ incurs significant cost in terms of power efficiency, throughput, computational power and delay. Unfortunately, such drawbacks can limit their applications to several current and emerging technologies. More specifically, the increasing number of wireless users has create spectrum scarcity, relying on small-size batteries create power constraints, deployment of real-time applications boost the demand for ultralow delay networks, and the ultra-small low-cost internet of things (IoT) devices has limited signal processing and computation capabilities. Consequently, extensive research efforts have been dedicated to overcome the limitations inherent in HARQ. This survey paper provides an extensive literature review of the state-of-the-art HARQ techniques and discusses their integration in various wireless technologies. Moreover, it provides insights on advantages and disadvantages of particular ARQ types and discusses open problems and future directions.

This paper presents a two-tier cellular structure with femtocells in open access mode. The addition of these base stations extends the offered system capacity and coverage area of the network. This two network parameters nowadays becomes rather important to provide Quality of Service (QoS) for data-hungry applications. Femto base stations (FBS) are deployed randomly to extend the coverage of conventional base stations. Since the femtocells are operating here in open access mode, so that the handover probability parameter becomes important concern. In this article, we declare the handover probability using the fundamentals of stochastic geometry.

This research work explores small cell densification as a key technique for next generation wireless network (NGWN). Small cell densification comprises space (i.e, dense deployment of femtocells) and spectrum (i.e., utilization of frequency band at large). The usage of femtocells not only improves the spectral efficiency (SE) of the Heterogeneous two-tier networks against conventional approach, but also it alleviates outage probability and enhances the achievable capacity. We yield an analytical framework to establish the density of the femto base station (FBS) to a monotonically increasing or decreasing function of distance or radius, respectively. This ensures the enhanced performance in spectrum sharing Orthogonal Frequency Division Multiple Access (OFDMA) femtocell network models. We also illustrate the influence of active Femto users (i.e., users in femtocells, and they are usually low mobility and located closer to the cell centre with less fading), cluster size (i.e., a group of adjacent macrocells which use all of the systems frequency assignments) via simulation results.

This paper explains genetic algorithm for novice in this field. Basic philosophy of genetic algorithm and its flowchart are described. Step by step numerical computation of genetic algorithm for solving simple mathematical equality problem will be briefly explained

In modern smart grids, the focus is increasingly shifted towards distributed energy resources and flexible electricity assets owned by prosumers. A system with high penetration of flexible prosumers, has a very large number of variables and constraints, while a lot of the information is local and non-observable. Decomposition methods and local problem solving is considered a promising approach for such settings, particularly when the implementation of a decomposition method features a market-based analogy, i.e. it can be implemented in a Transactive Energy fashion. In this paper we present an auction-theoretic scheme for a setting with non-convex prosumer models and resource constraints. The scheme is evaluated on a particular case study and its scalability and efficiency properties are tested and compared to an optimal benchmark solution. A game-theoretic analysis is made with respect to how an intelligent agent, that bids on behalf of a prosumer can try to strategize within the auction, in order to make itself better-off. Our simulations show that there is an alignment of incentives, i.e., when the prosumers try to strategize, they actually improve the auction's efficiency.

We propose an analytical framework of significant influence of deployment of femto base stations (FBSs) in a dual-tier network constituted of macro base stations (MBSs). As because of uncoordinated deployment, FBSs results in destructive interference to MBSs and viceversa. But, throughput efficiency of indoor (Femtocell) and outdoor (Macrocell) environment substantially increases due to an optimum reutilization of available spectrum. The quality of service (QoS) is further getting optimized in terms of throughput and network coverage because of incorporation of steerable beamforming. Finally, the effectiveness of the scheme is verified by extensive matlab simulation.

In this paper, we initially dealt with the issue of spectrum allocation among macro (or “licensed”) and Femto (or “unlicensed”) users in an Orthogonal Frequency Devision Multiple Access (OFDMA) based dual-layer femtocell networks. This research contribution will lead to basic coin in the design of next generation (5G) wireless networks. This manuscript exemplifies the trade off issue of energy efficiency (EE) and spectral efficiency (SE) with both cooperative and non-cooperative architecture in cognitive femtocell networks. The pivotal concepts for each technology are described, along with their potential impact on 5G and the research challenges that remain. Further, the trade-off between EE and SE is reposed with respect to the state of the art. The obtained insightful observations from the trade-off analysis of EE ans SE can lead to provide design guideline for 5G wireless Networks.

In this work, we present the cell edge coverage probability (CECP) performance of cellular networks under the composite multi-path fading environment, where Rayleigh fading is superimposed on lognormal shadowing, by the fractional frequency reuse (FFR) scheme. We demonstrate that our analytical results and the simulation results are in line with the analysis presented in [12].

In LTE-A (LTE-Advanced), the access network cell formation is an integrated form of outdoor unit and indoor unit. With the indoor unit extension the access network becomes heterogeneous (HetNet). HetNet is a straightforward way to provide quality of service (QoS) in terms better network coverage and high data rate. Although, due to uncoordinated, densely deployed small cells large interference may occur, particularly in case of operating small cells within the spectrum of macro base stations (MBS). This paper probes the impact of small cell on the outage probability and the average network throughput enhancement. The positions of the small cells are retained random and modelled with homogeneous Poisson Point Process (PPP) and Matérn Cluster process (MCP). The paper provides an analytic form which permits to compute the outage probability, including the mostly applied fast fading channel types. Furthermore, simulations are evaluated in order to calculate the average network throughput for both random processes. Simulation results highlights that the network throughput remarkably grows due to small cell deployment.

This work presents the evaluation of the downlink (DL) performance of a dual-layer cellular networks by using energy efficiency (EE) metric, where femto base stations (FBSs), macro base stations (MBSs) and users (FUs) form independent spatial Poisson point processes (PPPs). The proposed network model is developed by considering number of antennas at each BS alongside a single antenna at each user with the use of the conventional spectrum re-utilization approach. Then, Coverage probability and EE expressions for the duallayer cellular networks are exclusively derived analytically. It is also demonstrated that simulation results are almost in-line with the analytical one in the PPP-based model. While coverage probability deteriorates with less margin in the lower FBS density region compared to the scheme presented in [10] signalled not much turnaround of the network performance, EE in the lower and the upper FBS density regions are likely to remain between 6x10^-3 to 9.2 x10^-3 Bits/Joule and 4.6 x10^-3 to 7.1x10^-3 Bits/Joule, respectively. Proposed scheme tells us that it is firmly on course to match up with Vehicular Ad-hoc NETworks (VANET) applications without incurring high cost as EE, low latency, coverage probability and low power adaptability are back on good growth path.

The data used for this study may be obtained from the Demographic and Health Survey (DHS) Program website under the Data section at https://dhsprogram.com/data/dataset/Afghanistan_Standard-DHS_2015.cfm?flag=0

Non-orthogonal multiple access (NOMA) is shown to be the optimal channel access method and a strong candidate to be employed at the fifth generation (5G) and beyond networks. This paper studies direct transmission (DT) and cooperative transmission (CT) modes of operations in NOMA communications and proposes an investigation on evolving a cooperative transmission NOMA (C-NOMA) into a Hybrid transmission NOMA (H-NOMA) that can be used for design and deployment of relay based wireless networks, such as networks for Internet of Things (IoT) applications.

In this paper, we articulate the network coverage issues for both Femto Users (FUs) and Macro Users (MUs) located at cell edges. The cognitive-femtocell networks functioning under the vicinity of a macrocell frontier where the parameters such as pathloss, shadowing, Rayleigh fading have considered into the system model. The users, located at network border are positioned far apart from the Macro Base Station (MBS). This can be treated as the underprivileged users. The underprivileged users are to be facilitated by the femto cell base stations to provide uninterrupted QoS. We present on the overall outage probability of Single Input single Output (SISO) users and Single Input Multiple Output (SIMO) users, respectively, by taking several circumstantial components such as such as probability density function (PDF), location gap between base stations (BSs) and users, intra-tier interference and inter-tier interference into account. Further, evaluation has been extended by considering network throughput as the efficiency measures based on the sub-carrier and the power allotment in the dual tier network.