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Traffic characterization is an important means for Internet Service Providers (ISPs) to adapt and to optimize their networks to the requirements of the customers. Most network measurements are performed in the backbone of these ISPs, showing both, residential and business Internet traffic. However, the traffic characteristics of business and home users differ significantly. Therefore, we have performed measurements of home users at a broadband wireless access service provider in order to reflect only home user traffic characteristics. In this paper, we present the results of these measurements, showing daily traffic fluctuations, flow statistics as well as application distributions. The results show a difference to backbone traffic characteristics. Furthermore, we observed a shift from web and Peer-to-Peer (P2P) file sharing traffic to streaming applications. [ABSTRACT FROM AUTHOR]

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With 5G technology driving its expansion as the main infrastructure for pervasive connection, the Internet of Things (IoT) symbolises a paradigm-shifting interconnectivity of objects and devices. The increasing integration of IoT devices into our daily lives poses serious security and privacy risks. Every smart object in an urban setting is connected, which increases the vulnerability of IoT-based smart cities to various security risks. It is crucial to guarantee these digital urban settings' security and resilience, especially as cities become more computerised and have a dense population of linked devices. Ensuring the integrity and functionality of smart cities requires immediate attention to detecting and mitigating potential cyberattacks. This research presents an intrusion detection model derived from data extracted by simulating the SYNFLOOD attack scenario, a prominent form of Denial of Service attack in IoT security. The suggested detection model classifies, trains, and validates the imported data using the k-folds method and creates a unique detection model. The proposed model is fast and effectively enables all IoT networks to communicate information without compromising privacy. The model enhances the detection process by employing data preprocessing and balancing. In this work, the experiments' accuracy is stable, proving the model's success for the six used machine learning algorithms resulted in an excellent performance with an accuracy of 92.3% for the Decision Tree and Neural Network. [ABSTRACT FROM AUTHOR]

Wireless mesh networks (WMNs) are emerged as prominent solution to provide seamless connection to the internet. WMNs are typically used for providing broadband wireless internet access to a large number of users and networks. Guaranteeing the quality of service to end users with efficient resource utilization is a challenging issue in WMNs. To accomplish this, we propose a hybrid routing protocol for wireless mesh networks. It is a combination of intra cluster routing protocol (ICR) and inter cluster routing protocol for mesh networks (ICMR). Intra cluster routing protocol is intended to facilitate the communication between mesh clients within a same cluster and inter cluster routing protocol (ICMR) intended to facilitate the communication for mesh clients from different clusters. Intra cluster routing protocol is a proactive type of routing protocol and inter cluster routing protocol is a reactive type of routing protocol. The performance of the proposed protocol is analyzed and the results shown superior performance compared to baseline routing protocols in terms of throughput, end to end delay, packet delivery ratio and jitter. [ABSTRACT FROM AUTHOR]

A Wireless Internet-access Mesh NETwork (WIMNET) provides scalable and reliable internet access through the deployment of multiple access points (APs) and gateways (GWs). In this work, we propose a selective routing algorithm aiming at a hierarchical minimization of the operational cost and the maximal end-to-end delay. In particular, by deploying redundant APs/GWs in the network field, the WIMNET becomes robust to the link or AP/GW failure. However, these redundant APs/GWs increase the operational cost like the power consumption. By using Dijkstra algorithm and 2-opt algorithm, the proposed algorithm iteratively deactivates the deployed APs/GWs and performs the routing that reduces the maximal end-to-end delay based on the APs/GWs remaining active. The generated route meets the real-world constraints like fairness criterion. We further propose a cross-layer design to enhance the routing performance by exploiting the MAC-layer frame aggregation technique. The selective routing algorithm is then implemented in the WIMNET simulator proposed by our group. The numerical experiments demonstrate that in both indoor and open space environments, the proposed selective routing greatly reduces the operational cost, i.e., up to 80% APs/GWs can be deactivated. [ABSTRACT FROM AUTHOR]

This research proposes afresh wide bandwidth co-design approach of low noise amplifier (LNA) with active antenna for mobile (3rd, 4th and specially 5th generation) communication technologies. Three major approaches are used for binding this research. First approach proposes LNA designs made of cascaded common gate (CG) and common source (CS) stages with proposed image network technique. This novel technique observed inverse impedance at output of image network in proposed designs that provides wide bandwidth at the desired band of operation. Single CG stage with image network achieves 3G 1st band for the fixed wireless internet access while addition of T-network as an output stage to CG succeed 3G 2nd band for mobile broadband access. Moreover, cascaded CG and CS stages with proposed technique provides 4G wide bandwidth within range of 2-8 GHz which could be occupies high speed data rate. While the displacement of inductors into microstrip lines in the proposed LNA design achieves much higher bandwidth from 2 to 18 GHz and could be provides best solution for information carrying capacity in the 5G mobile technology. In second approach, asymmetric F-shaped slotted antenna is design which obtained bandwidth from 10.7 to 14 GHz within desired receiving direction. Finally, integration of proposed LNA design with F-shaped slotted active antenna provides co-design receiver and obtains minimum attenuation with highest gain. Entire proposed designs are implemented into ADS platform using commercial available RF-mixed 65 nm CMOS process. Measured results of chip design for proposed LNAs under the power consumption of 7.3 mW with fixed operating voltage of 0.9 V made good correlation with the simulation results. [ABSTRACT FROM AUTHOR]

This paper demonstrates the analytical approach of Linearized Radio over Fiber (RoF) link based on Dual-Drive Dual Parallel Mach Zehnder Modulator (DD-DPMZM) by properly adjusting the phase shifters and biasing of the Mach Zehnder Modulator (MZM). Two input RF Source at 7 and 8 GHz applied in the used RoF link. The proposed RoF link consists of Mach Zehnder Modulator (MZM), Parallel combination of Mach Zehnder Modulators, optical fiber, and photodetector (PD). Third Order Intermodulation Distortions (IMD3) factor act as a major issue, which is responsible as performance degradation factor. Major sources of IMD3 spurious components have been investigated and suppressed in theoretical analysis before photodetection. The proposed method is designed with the help of OptSim simulation software, to confirm and validate the analytical analysis and simulation results. Analytical analysis & simulation results show that, 40 dB suppression found in IMD3 spurious components, and 30 dB.Hz2/3 enhancement found in Spurious Free Dynamic Range (SFDR), for the proposed linearized RoF link as compared to conventional MZM RoF link. The Measured SFDR is also founded as 26 dB.Hz2/3, 5 dB.Hz2/3, & 10 dB.Hz2/3 for different optical fiber impairments as 8 km, 10 km & 15 km respectively for used DD-DPMZM based RoF link. [ABSTRACT FROM AUTHOR]

An efficient Media Access Control ( MAC) protocol for wireless Internet access is developed in this study. The proposed access protocol exploits the fact that very often the Internet access messages, such as HTTP download requests, are based on short packets. In addition, whenever the user is able to access to multiple overlapping base stations (e.g., in WiMAX access networks, or in 3GPP cellular networks), the proposed protocol enables the user to select the least loaded base station. Consequently, the user gets a better quality of service, while load balancing is achieved by preferring links that are less loaded over congested links. The key idea is to adjust the access probability to the load on the local link, and to use a different access protocol for short messages. Delay insensitive and long messages are transmitted using a Request To Send ( RTS) and Clear To Send ( CTS) mechanism, in a similar way to IEEE 802.11, over hops that are able to support this protocol type, while short and delay-sensitive messages are transmitted using another method, that offers a reduced call delivery delay, as well as better channel utilization. Whenever the message length drops below a certain threshold (evaluated in this study), the overhead of transmitting an RTS and CTS messages becomes too large. The analysis in this study shows that this threshold is load-dependent. Whenever the message length drops below this load-dependent threshold, this study proposes to use a protocol which is more efficient for short messages transmissions, such as HTTP download requests, Short Message Service (SMS) messages, and signaling messages. The proposed MAC protocol is especially suitable for 3G and beyond cellular networks. Whenever there are number of channels that can be possibly used to deliver a message, it enables to select the least loaded channel among several channels. [ABSTRACT FROM AUTHOR]

A performance evaluation is presented for a split-connection protocol for wireless Internet access which is denoted Split-Connection Mobile Tranport Protocol (SCMTP). It uses the general approach of the previously introduced Mobile End Transport Protocol (METP) but with differences that include a wireless-link channel-access protocol better matched with current cellular networks and more general ARQ methods for error control in the wireless link. In common with METP, SCMTP uses a standard TCP protocol on the wire-line connection and isolates the data flow in the wire-line network from the effect of wireless packet errors.Performance is considered for the important case of a single SCMTP split connection between a fixed host and a mobile host with heavy downlink traffic from the fixed host to the mobile host. It is shown for these conditions that if the wire-line packet-error rate is small, a steady state is reached in which the connection's data flow in the wire-line network remains under the control of the receiver-advertised window of the TCP entity at the base station. Performance is evaluated for the steady-state operation of the SCMTP protocol, and relationships are established between the key properties of the split connection and the end-to-end performance of the connection.It is shown that for heavy downlink traffic, the delay in the wire-line part of the connection does not affect steady-state throughput if the receiver buffer is sized appropriately. It is also shown that use of the go-back-N ARQ protocol on the wireless link yields better performance than the stop-and-wait ARQ protocol, although the performance with go-back-N ARQ is more sensitive to the characteristics of the wireless channel. It is shown that under a broad range of conditions, SCMTP with go-back-N ARQ provides nearly optimal utilization of the capacity of the wireless link. [ABSTRACT FROM AUTHOR]

Purpose of Review: To review randomized controlled trials (RCTs) published from 2021–2023 that reported the effects of peer support interventions on outcomes in patients with type 2 diabetes (T2DM). Recent Findings: Literature searches yielded 137 articles and nine RCTs were ultimately reviewed. The reviewed trials involved in-person support groups, peer coach/mentor support, cultural peer support by community health workers, peer support during shared medical appointments (SMAs) including virtual reality-based SMAs, telehealth-facilitated programs, and telephone peer support. Most interventions combined two or more peer support strategies. Peer support was associated with significant decreases in HbA1c in 6 of the 9 reviewed studies. The largest statistically significant improvements in HbA1c were reported in a study of community health workers in Asia (-2.7% at 12 months) and a Canadian study in which trained volunteer peer coaches with T2DM met with participants once and subsequently made weekly or biweekly phone calls to them (-1.35% at 12 months). Systolic blood pressure was significantly improved in 3 of 9 studies. Summary: The findings suggest that peer support can be beneficial to glycemic control and blood pressure in T2DM patients. Studies of peer support embedded within SMAs resulted in significant reductions in HbA1c and suggest that linkages between healthcare systems, providers, and peer support programs may enhance T2DM outcomes. [ABSTRACT FROM AUTHOR]

Wireless data network has experienced tremendous growth in the past few years. One of the common scenarios of using data wireless data network is while travelling in a train. Providing in-train wireless Internet access to multimedia applications (e.g., youtube) requires 3G/4G networks. While 3G/4G networks provide fast data access when users are static, it has significant latency when being used on the train. This is because 3G/4G networks use Mobile-IP that requires mobile nodes to register to foreign agents when handover occurs. This will introduced latency for the handover process. When registration is done, Mobile-IP suffers from triangular routing, which further decreases its performance. In this paper we argue that railway networking can be more effective through named data networking (NDN). Rather than using IP addresses, NDN provides a name-based paradigm that can achieve seamless handover. We analyze how NDN can support efficient handover and conduct simulation to test its performance. Results show the efficiency of NDN. [ABSTRACT FROM AUTHOR]

This paper proposes a wireless network-based machine intelligence model to enhance the predictive capability of green tourism satisfaction in regions with cultural differences. The model combines big data analysis techniques and machine learning algorithms to collect tourist data through intelligent machines and devices. Analyzing tourists' behavior and preferences establishes a reliable prediction model to effectively assess tourists' satisfaction with green tourism. Additionally, the paper constructs a distributed integration scheduling and feature mining model of green tourism satisfaction, which extracts relevant information features of big statistical data using an integration feature detection method. Furthermore, the paper establishes a fuzzy network structure model and designs the objective function of green tourism satisfaction prediction through decision scheduling and parameter optimization. The model's parameter-weighted learning enhances the optimization prediction ability of green tourism satisfaction under regional cultural differences. The paper also carries out green tourism satisfaction prediction and tourists' preference feature analysis using the fuzzy big data matching feature clustering method. The fuzzy network block fusion and clustering results also enable tourists' preference behavior feature analysis, further improving the predictive capability of green tourism satisfaction under regional cultural differences. The simulation results demonstrate high accuracy and good optimization ability, ultimately improving green tourism satisfaction prediction. [ABSTRACT FROM AUTHOR]

Few years ago some network operators launched a new service called Community Networks, where each subscriber shares its residential Internet connection with other subscribers of the same operator via his 802.11 access point. Due to the high access point density in urban areas, community networks have the potential to offer high data rate wireless Internet access for mobile users, going beyond the currently available hot-spots, which are typically deployed in a limited number of isolated locations (e.g., airports, cafes). Unlike cellular networks, the locations of community network access points is not centrally planned. We evaluate existing community networks using a participatory sensing application called Wi2Me. First, we analyze different metrics in order to characterize community networks. Second, we take advantage of this unique 802.11 network (in terms of density and coverage) to study how mobility can be supported by identifying drawbacks and proposing some possible solutions. [ABSTRACT FROM AUTHOR]

Wireless Mesh Networks (WMNs) are an important networking infrastructure for providing cost-efficient broadband wireless connectivity to a group of users. WMNs are increasingly being used in urban, metropolitan and municipal area networks for deployment of medical, transport, surveillance systems, etc. The performance and operability of WMNs largely depends on placement of mesh routers nodes in the geographical area to achieve network connectivity and stability. The objective is to find an optimal and robust topology of the mesh router network to support intelligent telecommunication services to clients such as adaptive and flexible wireless Internet access, mobile data, voice, video in addition to supporting other preferred client services. In this work, we propose and evaluate local search methods for intelligent placement of mesh routers in WMNs with a two fold objective: maximizing the size of the giant component in the network and user coverage. Given a grid area where to distribute a given number of mesh router nodes, which can have different radio coverage, and a number of fixed clients a priori distributed in the given area, local search methods explore different local movements and incrementally improve the quality of the router nodes placement in terms of network connectivity and user coverage. We have experimentally evaluated the proposed local search methods through a benchmark of generated instances of varying sizes. Moreover, different distributions of mesh clients (Uniform, Normal, Exponential and Weibull) are used. The experimental evaluation showed the good performance of local search methods for optimizing network connectivity and user coverage in WMNs. [ABSTRACT FROM AUTHOR]

Interworking UMTS and WiMAX networks offers global roaming and cost effective broadband wireless Internet access. Designing efficient Intra and Inter WiMAX handovers in the interworking architecture is a challenging problem. Handovers must be instantaneous and secure at the same time. We attempt to solve this problem by designing Intra and Inter WiMAX handover protocols which are capable of operating in the UMTS-WiMAX interworking architecture and perform mutual pre-authentication between the mobile station and the target network prior to handover. Due to the pre-authentication procedure, our proposed handover protocols outperform standard handover protocols by dispatching fewer handover signaling messages, experiencing less handover delay and preserving computation resources of critical nodes in the interworking architecture. Furthermore, our proposed handover protocols meet essential security requirements and defend against common attacks affecting handover protocols. [ABSTRACT FROM AUTHOR]

IEEE 802.11 Wireless LAN (WLAN) has become a prevailing solution for broadband wireless Internet access while the Transport Control Protocol (TCP) is the dominant transport-layer protocol in the Internet. Therefore, it is critical to have a good understanding of the TCP dynamics over WLANs. In this paper, we conduct rigorous and comprehensive modeling and analysis of the TCP performance over the emerging 802.11e WLANs, or more specifically, the 802.11e Enhanced Distributed Channel Access (EDCA) WLANs. We investigate the effects of minimum contention window sizes and transmission opportunity (TXOP) limits (of both the AP and stations) on the aggregate TCP throughput via analytical and simulation studies. We show that the best aggregate TCP throughput performance can be achieved via AP’s contention-free access for downlink packet transmissions and the TXOP mechanism. We also study the effects of some simplifying assumptions used in our analytical model, and simulation results show that our model is reasonably accurate, particularly, when the wireline delay is small and/or the packet loss rate is low. [ABSTRACT FROM AUTHOR]

Nowadays Wi-Fi is the most mature technology for wireless-Internet access. Despite the large (and ever increasing) diffusion of Wi-Fi hotspots, energy limitations of mobile devices are still an issue. To deal with this, the standard 802.11 includes a Power-Saving Mode (PSM), but not much attention has been devoted by the research community to understand its performance in depth. We think that this paper contributes to fill the gap. We focus on a typical Wi-Fi hotspot scenario, and assess the dependence of the PSM behavior on several key parameters such as the packet loss probability, the Round Trip Time, the number of users within the hotspot. We show that during traffic bursts PSM is able to save up to 90% of the energy spent when no energy management is used, and introduces a limited additional delay. Unfortunately, in the case of long inactivity periods between bursts, PSM is not the optimal solution for energy management. We thus propose a very simple Cross-Layer Energy Manager (XEM) that dynamically tunes its energy-saving strategy depending on the application behavior and key network parameters. XEM does not require any modification to the applications or to the 802.11 standard, and can thus be easily integrated in current Wi-Fi devices. Depending on the network traffic pattern, XEM reduces the energy consumption of an additional 20–96% with respect to the standard PSM. [ABSTRACT FROM AUTHOR]

Abstract  In this paper, we present a packet scheduling algorithm for a non-real-time service, with soft QoS requirements, which allows for degrading the QoS level, e.g., typically the packet delay, whenever necessary, in mobile broadband wireless Internet access systems. This algorithm is designed to properly trade off system throughput and delay performance, which can improve the system capacity by relaxing the delay constraint with respect to the underlying soft QoS requirement. This is as opposed to most of the existing packet scheduling algorithms for non-real-time service which are simply designed to maximize the system throughput without a delay constraint. The proposed adaptive exponential scheduling algorithm intentionally introduces additional delay to some users, especially under bad channel conditions, opportunistically allowing for serving users only under good channel conditions, as long as the resulting QoS degradation is acceptable for non-real-time service users. The results from a system-level simulation demonstrate that the system capacity can be significantly increased over existing algorithms, by as much as 65%, using the adaptive exponential scheduling algorithm while satisfying the given QoS-level requirements. [ABSTRACT FROM AUTHOR]

This paper presents an intelligent mobility management scheme for Mobile Wireless InterNet – MWIN. MWIN is a wireless service networks wherein its core network consisting of Internet routers and its access network can be built from any Internet-capable radio network. Two major standards are currently available for MWIN, i.e., the mobile IP and wireless LAN. Mobile IP solves address mobility problem with the Internet protocol while wireless LAN provides a wireless Internet access in the local area. However, both schemes solve problems independently at different layers, thereby some additional problems occur, e.g., delayed handoff, packet loss, and inefficient routing. This paper identifies these new problems and performs analyses and some real measurements on the handoff within MWIN. Then, a new handoff architecture that extends the features of both mobile IP and wireless LAN handoff mechanism was proposed. This new architecture consists of mobile IP extensions and a modified wireless LAN handoff algorithm. The effect of this enhancement provides a linkage between different layers for preventing packet loss and reducing handoff latency. Finally, some optimization issues regarding network planning and routing are addressed. [ABSTRACT FROM AUTHOR]

One challenge in the development of telecommunication networks is the seamless integration of wireless devices into the global Internet. Although it is well known that the Internet protocols were designed for heterogeneous networks an end-system with the usual Internet protocol stack will suffer an inefficient communication while connected via a wireless link. The protocol mechanisms of the transport layer can lead to poor performance in case of TCP and a high loss rate in case of UDP. In this paper we advocate a Remote Socket Architecture (ReSoA) which is a kind of proxy-oriented architecture for wireless Internet access in Wireless LAN environment. This approach allows the use of a thin protocol stack on the wireless end-system to save scarce resources and a tailored protocol for the wireless link without breaking the original TCP semantics. We show the suitability of ReSoA by comparing its performance with that of pure TCP and Berkeley Snoop through actual measurements in a test environment. [ABSTRACT FROM AUTHOR]

Treating patients with up-to-date medical knowledge is an ongoing goal for healthcare workers and implies efficient knowledge management at the point of care. Widely available mobile wireless technologies influence practices but a significant gap remains between technological possibilities and actual usage. The purpose of this study was to analyze residents' baseline practices in managing medical knowledge and to evaluate the use and impact of an innovative multiplatform application dedicated to anesthesiology and intensive care residents. This study took place in Rennes Teaching Hospital and comprised two distinct surveys. First, in April 2018, all residents received a ten-items online survey focusing on managing medical knowledge. Then, through a second online survey constituted of ten items, we sought to assess the use of a new multiplatform cloud-based application named "DansMaBlouse", dedicated to sharing and indexing medical knowledge, in anesthesiology and intensive care residents. Among 148 residents that answered the evaluation survey, the most sought out pieces of information in clinical setting were a phone or fax number (74%), drugs' characteristics (68%) and expert guidelines (57%). The main sources were senior staff (68%), medical databases (60%) and an Internet search engine (59%). Computers and smartphones were more frequently used than bound paper notebooks. After implementation of the multiplatform application DansMaBlouse, fifty-nine (82%) of the 72 residents that answered the evaluation survey reported using the application and 39% used it more than ten times. Among application users, 90% found it easy to use and 92% agreed that it improved point-of-care access to knowledge. Accessing appropriate medical knowledge at the point of care remains an issue for residents and can be improved by a multiplatform application combining personal and shared up-to-date resources. [ABSTRACT FROM AUTHOR]

Social robots are increasingly used in the care of older adults, including people living with dementia. An important prerequisite for effective use is knowledge about which factors facilitate and hinder the acceptance of social robots. The aim of this review at the intersection of health care research and human–robot interaction research is to understand factors facilitating and hindering the acceptance of social robots for older adults and people living with dementia in nursing homes based on the Almere model and to identify research gaps. We conducted a scoping review, systematically searching MEDLINE, PsycINFO, CINAHL and Compendex. The Almere model of acceptance was used to guide the development and conduct of this review. We used the principles of deductive content analysis, and we narratively present the review results. Twenty-six studies were included in the review. We found facilitating and/or hindering factors for all constructs of the Almere model. Perceived usefulness, perceived ease of use and perceived enjoyment were the most studied constructs, whereas trust and intention to use were the least studied constructs. Across constructs, seeing robots positively impacting residents was one of the key facilitating factors, and practical difficulties were a hindering factor. The Almere model provided useful insight into the acceptance of social robots. Nevertheless, we found the concept of engagement, the nursing home context, the intervention characteristics and the individual user groups important for the acceptance of social robots in nursing homes and therefore argue for future research expanding on the model. [ABSTRACT FROM AUTHOR]

A growing number of schools have recently been changing their culture of teaching and learning towards personalized learning. Our study investigates how schools use digital technology to facilitate and promote personalized practices. Based on the answers of a student questionnaire from 31 lower-secondary schools with a personalized learning policy in Switzerland, we selected the three cases with the most frequent use of digital technology in the classroom. Using key categories of digital technology implementation to frame the analysis, we examined the differences and similarities regarding the contribution of digital technology to fostering personalized learning. A systematization of our analyses resulted in three different types in terms of how schools integrate digital tools into their daily practices: 1. selective use of digital technology according to individual teacher preference; 2. selective use of digital technology according to individual student preference; and 3. structural use of digital technology in accordance with a school-wide strategy. The findings provide indications for future research and practice with respect to an implementation of personalized learning that takes full advantage of digital technology. [ABSTRACT FROM AUTHOR]

Is remote learning associated with education inequalities? We use PISA 2018 data from five European countries—France, Germany, Italy, Spain and the United Kingdom—to investigate whether education outcomes are related to the possession of the resources needed for distance learning. After controlling for a wide set of covariates, fixed effects, different specifications and testing the stability of coefficients, we find that remote learning is positively associated with average education outcomes, but also with strong and significant education inequalities. Our results show that negative gaps are larger where online schooling is more widespread, across countries, locations, and school types. More generally, remote learning inequalities appear to be associated with technological network externalities: they increase as digital education spreads. Policy makers must guarantee to all students and schools the possession of the resources needed for remote learning, but to reach this goal efficiently they must adapt their actions to the characteristics of countries, areas and school systems. [ABSTRACT FROM AUTHOR]

Farming has a plethora of difficult responsibilities, and plant monitoring is one of them. There is also an urgent need to increase the number of alternative techniques for detecting plant diseases, which is now lacking. The agriculture and agricultural support sectors in India provide employment for the great majority of the country's people. In India, the agricultural production of the country is directly connected to the country's economic growth rate. In order to sustain healthy plant development, a variety of processes must be followed, including consideration of environmental factors and water supply management for the optimal production of crops. It is inefficient and uncertain in its outcomes to use the traditional method of watering a lawn. The devastation of more than 18% of the world's agricultural produce is caused by disease attacks on an annual basis. Because it is difficult to execute these activities manually, identifying plant diseases is essential to decreasing losses in the agricultural product business. In addition to diagnosing a wide range of plant ailments, our method also includes the identification of infections as a prophylactic step. Below is a detailed description of a farm-based module that includes numerous cloud data centers and data conversion devices for accurately monitoring and managing farm information and environmental elements. This procedure involves imaging the plant's visually obvious signs in order to identify disease. It is recommended that the therapy be used in conjunction with an application to minimize any harm. Increased productivity as a result of the suggested approach would help both the agricultural and irrigation sectors. The plant area module is fitted with a mobile camera that captures images of all of the plants in the area, and all of the plants' information is saved in a database, which is accessible from any computer with Internet access. It is planned to record information on the plant's name, the type of illness that has been afflicted, and an image of the plant. In a wide range of applications, bots are used to collect images of various plants as well as to prevent disease transmission. To ensure that all information given is retained on the Internet, data is collected and stored in cloud storage as it becomes essential to regulate the condition. According to our findings from our research on wide images of healthy and ill fruit and plant leaves, real-time diagnosis of plant leaf diseases may be done with 98.78% accuracy in a laboratory environment. We utilized 40,000 photographs and then analyzed 10,000 photos to construct a DCDM deep learning model, which was then used to train additional models on the data set. Using a cloud-based image diagnostic and classification service, consumers may receive information about their condition in less than a second on average, with the process requiring only 0.349 s on average. [ABSTRACT FROM AUTHOR]

The development of new technologies such as the Internet of Things and cloud computing tests the transmission capabilities of communication networks. With the widespread application of multiple wireless access technologies, it has become popular for modern communication devices to be equipped with multiple network access interfaces. The increasing of various network attacks significantly reduces the robustness of multipath TCP (MPTCP) transport systems. To address this problem, this paper proposes a network traffic anomaly detection model based on MPTCP networks, called MPTCP-EMD. The model combines multi-scale detection and digital signal processing theory to implement anomaly detection based on the self-similarity of MPTCP network traffic. It uses the empirical modal decomposition (EMD) method to decompose MPTCP traffic data and reconstruct the valid signal by removing high-frequency noise and residual trend term. Using the idea of sliding windows, the model then compares the changes in the Hurst exponent of the MPTCP network under different attack conditions to determine whether anomalies have occurred. The simulation results show that the EMD method can be used for anomaly detection of MPTCP network traffic. The Hurst exponent of the attacked MPTCP network significantly exceeds the range of the unattacked network, and exhibits significant jitter. [ABSTRACT FROM AUTHOR]

Importance of spectrum regulation and management was first revealed on May of 1985 after the release of unlicensed ISM bands resulting in emergence of Wi-Fi, Bluetooth and many other wireless technologies that has affected our daily lives by enabling the emergence of the smart world and IoT era. Today, the idea of a liberated spectrum is circulating around, which can potentially direct wireless networking industry into another revolution by enabling a new paradigm in intelligent spectrum regulation and management. The RF signal radiated from IoT devices as well as other wireless technologies create an RF cloud causing co- and cross-interference to each other. Lack of a science and technology for understanding, measurement, and modeling of the RF cloud interference in near real-time results in inefficient utilization of the precious spectrum, a unique natural resource shared among all wireless devices of the universe in frequency, time, and space. Near real time forecasting of the RF cloud interference is essential to pursue the path to the optimal utilization of spectrum and a liberated spectrum management. This paper presents a historical perspective on the evolution of spectrum regulation and management, explains the diversified meanings of interference for different sectors of the wireless industry, and presents a path for implementing a theoretical foundation for interference monitoring and forecasting to enable the emergence of a liberated spectrum industry and a new paradigm in spectrum management and regulations. [ABSTRACT FROM AUTHOR]

Based on the sharing economy, crowdsourcing logistics services share social delivery freelancers instead of traditional full-time delivery employees. The optimal dynamic pricing model of crowdsourcing logistics services, which could be applied to adjust the social delivery capacity supply to meet the stochastic demand especially during the peak period, is established based on optimal control theory. We study optimal pricing strategies under both conditions when the supply and the demand is balanced and accumulated delivery orders are minimized. Moreover, the impact of delivery riders' wage ratio on pricing and platforms' expected revenue are analyzed. It is verified by numerical simulation results that optimal dynamic pricing strategies of crowdsourcing logistics services could effectively balance supply and demand, further maximize the expected revenue of platforms. The growth rate of optimal pricing of crowdsourcing logistics services is increasing with respect to the delivery riders' wage ratio. However, the expected revenue of crowdsourcing logistics platforms declines as the wage ratio increases. [ABSTRACT FROM AUTHOR]

The main objective of the study was to understand specific ways in which a flexible, technology-enhanced space can create opportunities for student engagement. Despite a few studies that address classroom elements such as furniture, researchers argue for more-holistic attention to the materials of learning environments to better support the activities in which students engage. To address this gap, we designed this qualitative case study of the role of the physical structure of flexible classrooms on college students' engagement. Findings from the analysis of the data can be classified into three areas: (a) flexible room layout and movable furniture enabled participants to create settings that could support students' group interactions; (b) flexible room layout and movable tools enabled people to move around to enhance student–to–student and teacher–to–student interaction; and (c) through the movement of furniture and tools and movement of people, participants were able to easily transition between different activities. The easy movement of tools and furniture widens the range of available classroom configurations to optimize engagement opportunities. Similarly, the flexibility of the classroom allows for the relatively easy movement of people. Our data suggest that such flexibility can facilitate interaction and engagement among students and instructors to create opportunities to promote both cognitive and emotional engagement. Findings underscore the critical role of space, furniture, and tools in the creation of learning environments that support student engagement in higher-education settings. [ABSTRACT FROM AUTHOR]

A recent market prediction is that 5G Fixed Wireless Access (FWA) will more than double over the next five years and trials at the same period in London suggest promising results. However, the shift to 5G FWA has raised a new set of research challenges in relation to speed of deployment and re-deployment, coverage, power consumption, end user mobility and last mile connectivity, to name just a few, because of the much higher expectations. A recent review reveals that key 5G Physical Layer technologies that will enable wide mobile and FWA have not kept up pace. In response to some of those research challenges, this paper presents the design of a 5G Multiple Input Multiple Output (MIMO) Antenna that is mounted on a tethered aerostat, and the combination of which serves as a 5G FWA aerial station. The antenna design features several novelties and the aerial station can provide last mile connectivity to a wide coverage footprint, with moderate power consumption and operating at high speeds. Both the evaluation of the antenna performance using several key performance indicators and the validation of the aerial station as a 5G FWA in a wireless sensor network (WSN) proof-of-concept application reveal efficiency gains. [ABSTRACT FROM AUTHOR]

Dramatic increases in public Wi-Fi™ (hereafter referred to as Wi-Fi) availability have occurred over the last decade. Although Wi-Fi provides convenient network connectivity, it has significant security vulnerabilities. Despite widespread knowledge of potential vulnerabilities of public Wi-Fi, most people simply connect to it in public places. We investigated the individual calculus behind risk-taking behavior based on the theoretical foundations of risk taking behavior, technology threat avoidance theory, prospect theory, and self-determination theory. Using survey data collected from 1313 respondents in the United States, this study found that avoidance motivation, risk averting propensity, and intrinsic and extrinsic motivations affect intention to use public Wi-Fi. In addition, our results indicate that avoidance motivation is related to safeguard effectiveness, safeguard cost, and perceived threat, while risk averting propensity is associated with positive outcome history, age, gender, and education attainment. [ABSTRACT FROM AUTHOR]

Open distance e-learning (ODeL) is an essential form of e-learning for students in South Africa. It allows expanded access to higher education for students from rural or socioeconomically disadvantaged backgrounds. One of the key features of ODeL is that students can complete coursework modules virtually, without the need to step onto a physical university campus. Students from rural areas are able to participate in higher education, something they otherwise would not have had access to without ODeL. Information and Communication Technologies (ICTs), including messaging apps like WhatsApp, provide students with informal and formal learning opportunities, increase access to academic and community resources, and mitigate some Internet connectivity issues. Students are able to use WhatsApp to build connections with students and share class materials, without access to an Internet-connected computer. Using ICTs to enhance access to higher education is one way to bridge the wide socioeconomic gap in South Africa. This paper argues for additional non-Western research on socio-technical marginalization and access to ICTs for students enrolled at higher education institutions in South Africa. [ABSTRACT FROM AUTHOR]

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Given the prevailing state of cybersecurity, it is reasonable to understand why cybersecurity experts are seriously considering artificial intelligence as a potential field that can aid improvements in conventional cybersecurity techniques. Various progressions in the field of technology have helped to mitigate some of the issues relating to cybersecurity. These advancements can be manifested by Big Data, Blockchain technology, Behavioral Analytics, to name but a few. The paper overviews the effects of applications of these technologies in cybersecurity. The central purpose of the paper is to review the application of AI techniques in analyzing, detecting, and fighting various cyberattacks. The effects of the implementation of conditionally classified "distributed" AI methods and conveniently classified "compact" AI methods on different cyber threats have been reviewed. Furthermore, the future scope and challenges of using such techniques in cybersecurity, are discussed. Finally, conclusions have been drawn in terms of evaluating the employment of different AI advancements in improving cybersecurity. [ABSTRACT FROM AUTHOR]

In the past few decades, the academic research and industrial synergy is dramatically accelerating to conceptualize high data rate services. The congestion in the radio frequency (RF) spectrum has imposed many inherent limitations in the growth of future wireless networks. These limitations have spurred global research activities to open new parts of the electromagnetic wave spectrum. More researches and developments in new modulation schemes, channel modelling and signal processing techniques are yet to be explored. Optical wireless communication (OWC) has appeared as an emerging complementary technology to RF systems. It is deemed as a promising alternative to address RF spectrum congestion and enhance system's capacity. OWC has gained widespread attention due to its high confidentiality, large spectrum resources and strong resistance to electromagnetic interference (EMI). In this paper, we envisage OWC systems as a promising solution for the bandwidth shortage of RF spectrum. We have also discussed the current upsurge of diversified OWCs in fifth generation (5G) and Internet-of-Things (IoT) solutions which has spurred heated discussion for future technologies. In this study, we have outlined a holistic vision of several OWC enabling technologies and survey of potential issues in OWC systems. We investigate visible light communication (VLC) and free space optics (FSO) as potential implementation approaches for OWC systems. Generally, the intent of this extant study includes (i) potential features and classifications of OWC systems, (ii) key enabling technologies, (iii) link design requirements and modulation schemes, (iv) main impairments and solutions to reduce the impairments, and (v) security issues and techniques to secure OWC. At last, open research challenges and future research directions in OWC systems are investigated. In this regard, we believe this survey will be helpful to aggregate the research efforts and eliminate the technical uncertainties towards breakthrough novelties of OWC technologies. [ABSTRACT FROM AUTHOR]

The popularity of Android brings much functionality to its users but it also brings many threats. Repacked Android application is one such threat which is the root of many other threats such as malware, phishing, adware, and economical loss. Earlier many techniques have been proposed for the detection of repacked application but they have their limitations and bottlenecks. The issue of malware and duplicate apps affecting the smartphones are being reported on a large scale and has drawn the attention of many researchers. Major of these issues target Android-based phones. Repackaged apps are usually infected versions of popular apps. Adversaries download a popular Android app, and obtain the code using reverse engineering and then add their code (often malicious) to it and repackage and release the app. The existing methods focus primarily on the extraction of apps' behavior and comparing the same with their static code. These have the least chance of detecting the code obfuscation and the dynamic behavior of apps. Therefore, a framework of App-NTS is proposed which extracts the dynamic behavior of the apps from the network traffic analysis. The dynamic vantage point algorithm used for the comparative analysis of the apps' behavior, which significantly helps in reducing the time complexity. Experimental analysis has detected 365 repacked apps from 8645 apps that are downloaded from various online markets and have also brought dramatic results in terms of better performance with Mean Square Error value decreased by 41% and Log loss reduced by 35.2%. There is an increase in accuracy of 18.3% when compared to other states of the art techniques. [ABSTRACT FROM AUTHOR]