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The demand for the fastest communication is a key concern for IoT technology with recent advances in the Internet of Things (IoT). With the advent of 5G telecommunications networks, the request for the quality of service (QoS) satisfaction in IoT communication can be bridged. Henceforth, a large number of devices will not be under limited resource assignment through the integration of the 5G telecommunications network. In this article, we address the above limitation on allocation by machine-learning, called the Artificial Network of prominent IoT devices (ANN). The adoption of the rules in ANN implies the allocation of resources to the most important devices and reduces them on the basis of priority. The simulation was conducted to test the effectiveness of the fuzzy system with 5G resources allocated to the IoT model. The findings indicate that the ANN model is more resource-allocating and energy efficient than other methods.

In this paper, we propose a data aggregation back pressure routing (DABPR) scheme, which aims to simultaneously aggregate overlapping routes for efficient data transmission and prolong the lifetime of the network. The DABPR routing algorithm is structured into five phases in which event data is sent from the event areas to the sink nodes. These include cluster-head selection, maximization of event detection reliability, data aggregation, scheduling, and route selection with multi attributes decision making metrics phases. The scheme performs data aggregation on redundant data at relay nodes in order to decrease both the size and rate of message exchanges to minimize communication overhead and energy consumption. The proposed scheme is assessed in terms of packet delivery, network lifetime, ratio, energy consumption, and throughput, and compared with two other well-known protocols, namely “information-fusion-based role assignment (InFRA)” and “data routing for in-network aggregation (DRINA)”, which intrinsically are cluster and tree-based routing schemes designed to improve data aggregation efficiency by maximizing the overlapping routes. Meticulous analysis of the simulated data showed that DABPR achieved overall superior proficiency and more reliable performance in all the evaluated performance metrics, above the others. The proposed DABPR routing scheme outperformed its counterparts in the average energy consumption metric by 64.78% and 51.41%, packet delivery ratio by 28.76% and 16.89% and network lifetime by 42.72% and 20.76% compared with InFRA and DRINA, respectively.

In today’s world, the increasing cost of healthcare and tremendous growth of elderly population introduced a major issue for medical monitoring and healthcare applications. A tiny sensor attached outside/inside the human body in Wireless Body Area Sensor Network (WBASN) monitors the surrounding environment and function of human body. Meanwhile, the heat dissipated from antenna and sensor node’s circuitry and antenna deteriorates human tissue. Thus it is very important to design a routing protocol in WBASN by incorporating the effect of temperature into routing metrics. A WBASN consists of heterogeneous nodes; therefore, the routing protocols must be designed to balance traffic among these sensor nodes. Vital signals of human body require different quality of service for different data types. Thus designing QoS aware routing protocols is a challenging task. In this paper, conventional temperature and QoS aware routing protocols are compared and open issues in routing protocol design are discussed.

Internet of Things (IoT) deployed enormous amount of data. The most challenging research is scrutinizing the parking availability among the distributed traffic in smart city. Usage of IoT in smart city organization sector endureslarge amounts of data. Smart city has sectorized its infrastructure operation via IoT communications. Smart city is dumped with huge amount of traffic due to existence of large number of vehicles. So the issue prevail most commonly in smart city is traffic congestion, and this setback can be overcome by a novelty based proposed techniques. In this research, to overcome above setback, we project a voting based hybrid ensemble classification, new hybrid methodology. This hybrid framework is utilized to predict the accessibility of parking place. The experimental results of proposed method achieve the 96% of accuracy and the availability rate achieves 89% when compared to existing method hence achieving better results.

Nature has made a huge impact on human’s diurnal lives in finding solutions for complex problems. Majority of the people are receiving benefits by the advanced technologies. Without the aid of computers, it is hard to imitate the problem solving techniques being implemented by nature. Bio-mimicry is one such study which enables the researchers in solving human problems by emulating and mimicking nature. This emerging technology fetches its sources from bio-inspired engineering at various levels. BIC, short for bio-inspired computing or biologically inspired computation, found to be a broad term, which comprises different fields like computer science, mathematics and biology. Mix and match of various biological and computational processes is the reliable means for researchers in this regard and this leads to the convergence of two fields: computer science and biology. In recent past, the bio-inspired optimization algorithms are highly convincing to bring out best expositions for intricate snags by joining hands with machine learning. Along with BIC, swarm intelligence (SI) is also equally gaining importance. Bio-inspiring algorithms like ant colony algorithm, bat algorithm, cuckoo search, fire-fly algorithms, and particle swarm optimization possess extensive applications in almost all fields of science and engineering. Swarm intelligence is the collective behavior of decentralized, self-organized systems, though they are natural or artificial and it is based on meta-heuristic approach which generally pulls out an approximate optimal solution independent of the problems in less time. Nowadays, the information technology advancements induce felons to commit copious cybercrimes using cyberspace. More sophisticated cyber-defense systems are to be devised essentially, since (1) cyber-infrastructures are extremely open and prone to infringements and other intimidations and (2) human intervention and physical devices are not adequate to monitor and fortify the cyber-infrastructures. The ability to detect a wide variety of threats and adaptability to make quick real-time decisions, flexibility and robustness are the major expected qualities for these systems. Abundant BIC approaches incorporated with artificial intelligence (AI) using IOT plays a vital role in cybercrime detection and prevention. Let us have a cattle graze of few techniques of AI associated with bio-inspired computing and its futuristic scope over human community to combat cybercrimes and this review would pave the alleyway for forthcoming studies to cherry-pick algorithms based on fitment.

Spinel-NiMn 2 O 4 (NMO) nanofibers of high aspect ratio, high surface area (50 m 2 g −1 ) and homogeneous pore size distribution are fabricated by electrospinning process and characterized by XRD, FTIR, XPS, BET, FESEM, TEM techniques. Further, multifunctional properties (energy storage properties, magnetic and electrical properties) of NMO nanofibers are also examined. High specific capacitance (C s ) of 410 (±5) F g −1 at 1 A g −1 , good rate capability and high cycling stability (up to 5000 cycles) are demonstrated by NMO nanofibers. Furthermore, NMO-based solid-state symmetric supercapacitor (SSSC) shows a high C s of 170 (±5) F g −1 at 0.5 A g −1 in potential range of 0.0V–2.0 V and exhibits excellent energy density of ∼95 W h kg −1 and power density of 1030 W Kg −1 . The above storage properties i.e. high energy density and output voltage of 2.0 V are further supplemented by lighting up a red colored LED (1.8 V @ current 20 mA) at least for 5 min. The ionic diffusion coefficient of NMO based electrode is found to be ∼4.84 × 10 −11 cm 2 s −1 . Magnetic and dielectric properties of NMO nanofibers are also examined and results are discussed.

An important and modern trend in wireless network is managing and accessing in heterogeneous wireless networks structures effectively. Vertical handover or handoff technology is major and acting vital role in wireless communication, it has key challenging issues in wireless network, while handover gets call drop kind of latency and call quality minimization. So the communication networks needs an efficient and dynamic services and knowledge monitoring management to select network for handover of different network environments (example: WiMAX, WiFi, WLAN, etc.). In this paper we proposed the concepts of knowledgeable monitoring (KM-method), cognitive advisor (CA) and Advanced Handover Optimization (AHO) technique to improve effective network selection for seamless communication, while travels over heterogeneous wireless networks (HWN). KM-method monitoring and manage effective network selection and holding connected mobile nodes inform header files also maintaining re-initiate to next network information (network IP address, user ID, new path, etc.). CAVHO-Cognitive Advisor based Vertical Handover (VSH and V2H) and KM-methods perform and measures velocity and direction of mobility nodes through SRSS sequential Received Strength Signal. Also CA receives the nearest networks details of each another using nearest neighbouring concept with SDT ratio Algorithm. Optimization technique (AHO) performs dynamically balancing the threshold level of speed, load and quality based on Receiving signal strength and user preference. Simulation results of CAVHO Shows it secure and increases the handover probability of access also proposed system reduce delay and improve quality of services and throughput.

Porous nanofibric network of spinel CoMn2O4 (CMO) are fabricated by facile electrospinning process and characterized by XRD, BET, TGA, FTIR, FESEM, TEM, XPS techniques. CMO nanofibers are employed as supercapacitor electrode for first time which exhibits high specific capacitance (Cs) of 320(±5) F g−1 and 270(±5) F g−1 at 1 A g−1 and 5 A g−1, respectively in 1 M H2SO4. CMO nanofibers exhibit excellent cyclability (till 10,000 cycles @ 5 A g−1). To examine practical performance, solid-state symmetric supercapacitor (SSSC) is also fabricated using PVA-H2SO4 as gel electrolyte. The SSSC evinces high energy density of 75 W h kg−1 (comparable to Pb-acid and Ni-MH battery) along with high power density of 2 kW kg−1. Furthermore, a red colored LED (1.8 V @ current 20 mA) was lit for 5 min using single SSSC device supporting its output voltage of 2 V. This high performance of CMO in both aqueous and SSSC is attributed to one dimensional nanofibers consisting of voids/gaps with minimum inter-particle resistance that facilitates smoother transportation of electrons/ions. These voids/gaps in CMO (structural as well as morphological) act as intercalation/de-intercalation sites for extra storage performance, and also works as buffering space to accommodate stress/strain produced while long term cyclings.

Many tiny sensors connected together for gathering the information constitute Wireless Sensor Network (WSN). It plays prominent role in many applications like environmental monitoring, target tracking, defence, military, etc. In many of the situations, sensor nodes are highly battery operated. So it becomes important to have maximum lifetime of the network and to advocate this issue many energy efficient methodologies are already proposed. One of the prominent methods is buffer management protocol based on queue threshold technique which is widely used to prolong the network lifetime. In this paper, real time results are obtained by considering environmental monitoring application to study the various network parameters in terms of number of retransmission, synchronization bytes, processing time and energy. Obtained results depicts that the energy consumed is highly reduced which leads to improvement in network lifetime while considering the queue threshold model.

A major issue in Wireless Sensor Networks (WSNs) is the minimum availability of energy and hence reducing the amount of energy consumed is of greater interest. In WSN, large amount of energy is consumed during transmission and failure of nodes in sensor network is common. Here, a novel technique is proposed to reduce the node's energy consumption during data transmission using queue threshold based on N-Policy Priority Queueing Model (PQM) by taking failure of nodes into consideration. A sensor network model is developed analytically to evaluate the performance of the proposed scheme by means of energy consumption and delay by taking node failures into consideration. From the results, it is inferred the average energy consumption savings is about 43% for the optimal threshold value by taking node failures into consideration. Simulations are carried out and the results obtained show that the analytical and simulation results matches thus validating the accuracy of the analytical model.

An important challenge in WSN is the availability of energy since the devices are battery operated and hence minimizing energy is very important. Many works have been already proposed to prolong the lifetime of WSN which includes an energy minimization scheme based on N-Policy Model using queue threshold but this technique introduces higher mean delay. In this work, we propose a new scheme using queue threshold based on N-Policy Priority Queuing Model by considering channel contention into account which reduces the energy consumption of nodes during data transmission as well as mean delay since the packets are prioritized. Here proposed analytical model of a cluster based sensor network and analyze the performance of the scheme in terms of performance metrics such as average energy consumption and mean delay considering channel contention. the derived expression for the optimal value of threshold for which the node consumes minimum energy. Results show that the average energy consumption savings is 60% for the optimal threshold value when compared to no threshold condition by considering channel contention.

With the developing world of science, VANET (Vehicular AdHoc Networks) has been emerged as the most prominent field of research and obtained maximum attention towards it in the past decade. VANET is an wonderful technology which allowed the moving vehicles to connect and communicate with each other. Thus with the rising attention VANET is requested to provide real time High Definition(HD) video streaming with the intention of both entertainment and to get proper safety informations. Though this requirement has high benefits it is also enchained with additional issues making it challenging. The quality of the video streaming is measured by temporal and spatial factors. Keeping these factors in mind a new protocol has been proposed in this paper to deploy receiver based relay node selection along with congestion control technique. Thus the result has high quality video with high scalability and low delay performance.

In modern mobile world interoperability between different wireless networks is most essential one, which enables the mobile node to move across the different heterogeneous wireless system. For seamless connectivity of mobile node mobility management and location management is essential one. In mobility management handoff estimation plays a vital role. To make the handoff estimation, attributes such as bandwidth, delay, signal quality, and energy etc., are required. This paper introduces EMDAM approach to choose optimized attribute values based on Artificial Immune System. The result obtained through this approach is compared with the existing approaches like SAW, MEW, TOPSIS and GRA for analysis and evaluation of performance.

The incidence of postoperative urinary retention (PUR) has been reported to range from 1% to 22% in patients who have undergone laparoscopic inguinal hernia procedures. The objectives of this study were to determine the incidence of PUR and examine different risk factors that may be associated with the development of PUR in patients who have undergone laparoscopic inguinal hernia procedures.A retrospective chart review was performed on 350 patients. Demographics, comorbidities, and operative and postoperative information were collected in patients undergoing laparoscopic inguinal hernia repair by 3 general surgeons from 2007 to 2011. Statistical analysis was done on patient demographics, medical histories, anesthesia notes, and postoperative notes to identify risk factors for the development of urinary retention after laparoscopic inguinal hernia repair.Three hundred fifty consecutive patients who underwent laparoscopic inguinal hernia repairs were reviewed. Twenty-nine patients developed PUR, an incidence of 8.3%. Age ≥60 years and history of benign prostatic hyperplasia showed significance on multivariate analysis, with odds ratios of 3.0 and 11.0 respectively (P.05). Anesthesia time ≥2 hours (odds ratio, .75) was a contributing perioperative risk factor but only as an independent risk factor (P.05).History of benign prostatic hyperplasia, age ≥60 years, and anesthesia time ≥2 hours were significant independent risk factors for urinary retention after laparoscopic inguinal hernia repair. On multivariate analysis, only history of group and age ≥60 years showed significance. This is 1 of the largest studies to show that the development of PUR in laparoscopic inguinal hernia repair patients is a multifactorial process. Further studies should be conducted to corroborate our findings.

Multiple task migration is a process in network on chips are able to transfer the data from one cluster to another cluster, while transfer the data from one to another cluster message latency, migration latency and power consumption are problem encountered. New techniques virtual point to point Connections (VIPs) has been introduced that dedicates low power and low latency heavy communication flow created by multiple task migration mechanism. The proposed system scheme reduces total message latency, total migration latency, total network latency, power saving is achieved compared to the previously proposed task migration strategy for mesh multicomputer. Analyzing the results show that the proposed scheme reduces message latency by 16% and migration latency by 15%, while 13% power savings can be achieved.

Patients with inflammatory bowel disease, such as Crohn’s disease (CD), suffer from a threefold increase in the risk of venous thromboembolism. Small bowel, segmental bowel, or ileocolonic resection to treat Crohn’s disease can lead to rare complications of portal vein thrombosis (PVT), which can lead to further poor health outcomes, such as small bowel ischemia. The study attempts to find different risk factors that may be associated with postoperative complications of PVT in Crohn’s disease patients. In a 1 to 3 case–control study following Institutional Review Board approval, 13 Crohn’s disease patients with documented radiological postoperative diagnosis of PVT from 2004 to 2011 and 39 CD patients who did not have postoperative PVT were matched by retrospective chart review for patient demographics, preoperative course and workup, anticoagulant use, and operative procedure. Univariate analysis was performed to draw correlations on risk factors for the development of PVT. In the 13 CD patients with PVT, concurrent cancer, liver disease, and dyslipidemia were present in 23.1%, 23.1%, and 15.4% of the population, respectively. Compared to the 39 CD only patients, concurrent cancer, liver disease, and dyslipidemia were present in only 2.6%, 2.6%, and 0% of the population, respectively. Of the CD patients with PVT, 61.5% were on preoperative steroids compared to 28.9% of the CD only patients. PVT development in CD patients is correlated with concurrent cancer (p = 0.016), liver disease (p = 0.016), dyslipidemia (p = 0.012), and preoperative steroid usage (p = 0.036). Concurrent cancer, liver disease, dyslipidemia, and preoperative steroid usage were risk factors associated with the development of PVT in Crohn’s patients. Since there is limited literature on PVT in CD, more data needs to be collected, and additional studies should be done to further assess the prevention, diagnosis, and management of the disease.

The impact of both various binders and carbon additives on the electrochemical behavior of intermetallics-based (FeSn2, NiSb2, TiSnSb) negative electrodesvs.Li was evaluated and accurately studied for FeSn2. The formulation of the composite electrode allowed enhancement of both the capacity retention as well as the rate capability. CMC/VGCF (carboxymethyl cellulose/vapor grown carbon fiber) used as a binder/conductive additive allows retention of 100% of the specific capacity during 35 cycles at 2C rate (2Li h−1), whereas the fading is dramatic after only a few cycles at a low rate with classical powdered electrodes. Notably, an extra capacity is observed with CMC/VGCF. In the case of FeSn2, it is shown that the improvement of performance achieved with CMC/VGCF results from better efficiency of the conductive additive to form an electronic percolation web around the active material (AM) particles rather than from the buffering of the volume variations of the AM particles, contrary to the case of Si-based electrodes. The improved cycle life is also likely due to the better ability of CMC to cover the particles compared to PVDF (polyvinylidene fluoride), resulting not only in stronger interparticle bonding but also in a better SEI layer. It is suggested that the growing of an insulating SEI layer by the degradation of the liquid electrolyte is an important factor in the fading mechanism of FeSn2 composite electrodes. Finally, the aqueous processing of the FeSn2, NiSb2, and TiSnSb intermetallics-based composite electrodes is feasible.

Developments in cast irons have widened their applications even replacing steel for automotive parts. The higher hardness and certain degree of microstructural integrity of cast iron pose considerable problems in machining. Coated carbides with substrates suitable for machining cast iron and tougher grades of ceramics are the tools most suited for machining cast iron. Among the coated carbides, ZrO2 and TiN multi-layered coated K-type cemented carbides exhibit better machining performance. Tougher grades of hot pressed monolithic black ceramic (Al2O3 + TiC) composites can also be used for better machining performance. Chemical reactions encountered during machining limit the performance of Si3N4 and cold compacted plain Al2O3 tools while machining cast iron.

Cast irons find increasing applications in the production of several automotive components such as crankshafts, gears and the like. Ceramics are the ideal tools for machining cast iron. The present paper illustrates data on performance of ceramic tools in machining cast iron. It also illustrates certain scanning electron micrographs highlighting the wear mechanisms.