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In the present situation, the world's population continues to rise rapidly, while the cultivated land suitable for cultivation stays the same. It forces farmers to demonstrate innovative techniques that improve crop yields to sustain the increasing population. Preserving the health of crops is quite critical in this respect. Therefore, early detection of disease in crops seems to be very crucial to monitor disease and increase crop yield. In this paper, a deep Convolutional Neural Network (DCNN) model is proposed using Bayesian learning process for classification of the diseases in plants. Material used for this work consist of 20,639 images taken from plantVillage having 15 distinct classes of healthy and infected leaf images of potato, tomato and pepper bell. The key objective of this research is the introduction of Bayesian process at the top of residual network for efficient feature learning. An investigation was performed for comparison of proposed DCNN with the traditional classifiers in terms of accuracy, precision, recall and F-score and result indicated that the proposed model is an efficient tool for classification of diseases. Further, the prominent physical or chemical properties of nanomaterials have enabled their use as innovative and high-performance diagnostic tools for varied plant pathogens and other important disease biomarkers. Taking these as a pre processing step while acquiring the data set and combining it with proposed work enhances the performance. The proposed approach utilizes the features developed by CNN mostly in different hierarchies to use Bayesian framework and obtains the accuracy rate of 98.9% with no sign of overfitting.

Background: Energy consumption is an important parameter in wireless sensor networks since it affects the lifetime of sensor nodes. Methods: Battery powered wireless sensor networks cannot sustain for long hence impractical for real-time applications. With energy harvesting and relevant protocols, this issue of extending the lifetime of nodes has been solved largely. The performance can be enhanced further if proper traffic analysis and modeling are done as a proactive approach. Results: A proper understanding of the traffic dynamics provides a base for further network optimization and detection of anomalies within the network. Much of the reported work in energy harvesting based WSN till now, is to design the efficient protocols only, traffic analysis and modeling is the ignored parameter. In this paper traffic models appropriate for the energy harvesting based system have been analyzed and their performance is evaluated for a MAC protocol. Conclusion: Results show that Weibull distribution is the most useful model for traffic modeling in energy harvesting based wireless sensor networks.

Primary Subject area Global Child and Youth Health Background The current refugee crisis is described as the largest humanitarian crisis of all time. Refugees often face psychosocial complexity and multi-dimensional healthcare needs. Community-Based Participatory Research (CBPR) methods have been previously employed successfully in designing health programs for refugee children, youth and their families, and in building strong research partnerships in refugee communities. Objectives To review the evidence in the involvement of refugee adults, youth and children in CBPR processes. Design/Methods A scoping review was performed, using Arksey & O’Malley’s methodological framework. A literature search in Medline, PubMed, PsycINFO, CINAHL, Embase and Scopus for articles published until August 2020 was conducted. Articles were included if they focused on CBPR or Participatory Action Research as the methodological framework, had refugee involvement and discussed healthcare and health policy. Data extracted included ethno-racial data, country of origin, purpose of CBPR, refugee CBPR involvement and its influence on health care research and policy. Results 4125 articles were identified in the database searches. After removal of duplicates, 2077 articles underwent title and abstract review by two authors, yielding a kappa-statistic of 0.85. Fourteen studies were included in the final analysis. Of these, 35.7% (5/14) included refugee children/youth in their CBPR methods. The purpose of the CBPR methods for 60% (3/5) of the articles focused on mental health promotion-related strategies. The other 40% (2/5) of articles focused on reproductive health. Eighty percent (4/5) of the studies included refugees in the inception of the research problem and in knowledge translation efforts, whereas none were involved in seeking funding. All studies included refugee participants in the study design and engaging community/recruitment. However, there were varying degrees of involvement of refugees in the data analysis (40%, 2/5), knowledge translation (40%, 2/5) and scale up (20%, 1/5). All studies did not distinguish between the level of CBPR involvement of children and adolescents. Conclusion There is scarce literature describing the involvement of refugee children, youth and their families in research. CBPR has been identified as a methodology with the potential to make substantial contributions to improving health and well-being in traditionally disenfranchised population groups. As the needs of refugee communities are so diverse, efforts should be made to include refugees in all stages of the research process. This scoping review demonstrates that levels of involvement in CBPR processes amongst refugee children, youth and adults may not be differentiated, and as such, may conflate their needs and experiences. Barriers to full participation in research processes should be examined further in order to eliminate health disparities and build capacity amongst refugee communities.

FRET is a nonradiative process of energy transfer that is based on the dipole-dipole interactions between molecules that are fluorescent. Transfer of energy takes place rapidly from a donor molecule to an acceptor molecule in juxtaposition such as 0 to 10 nm without photonic radiation. FRET has occupied a center stage in biotechnology and biological studies. It is used to gain information on conformation changes in single molecules. The pharmaceutical industry has also developed large fluorescence detection systems with very small sample sizes, at the level of single molecules, using fluorescence correlation spectroscopy.

The wireless sensor network is one of the promising technologies in the agriculture field. Its actual usage in real agriculture fields is limited by its dependence on the small batteries which cannot make the network survive for long. Various protocols are being designed at the network and MAC layer to increase the lifetime of the nodes, but up to a certain extent only. Hence the energy harvesting to power up the WSN nodes is a promising technology to fulfill this ever energy demand, but the protocols need to be redesigned for this scenario. Solar energy harvesting based MAC protocol which is adaptive to the changing weather conditions is designed in this paper for the smart agriculture applications. It is based on the multilayer and receiver-initiated process to improve network quality. It has shown the remarkable performance over the other energy harvesting based protocols in terms of ENO ratio, energy consumption and collision rate.

Limited availability of energy is the most crucial constraint of wireless sensor networks (WSN). Most power consuming part of WSN node is transreceiver and operation of transreciever to access medium is controlled by the medium access control (MAC) sublayer of the open systems interconnection (OSI) model. In WSN, till now, most of the present MAC protocols have addressed issues related to power saving. Because of energy constraints, performance is often not a focused design parameter in these MAC protocols. However, recent advances in energy harvesting technology have made it possible to obtain energy from the environment to solve energy limitations. So in this paper, a new multi layer based MAC protocol, MLMAC-HEAP is designed for solar energy harvesting criterion considering performance as the mainly focused parameter. Performance is illustrated in terms of throughput. This paper evaluates the performance of MLMAC-HEAP as a function of energy harvesting rate and number of nodes in network and results are compared and shown to outperform well known MAC protocols. Then, the paper analyses the protocol for various traffic models. Based on application-level requirements, optimization is also done for number of layers.

Now a day, liver disease is common disease due to the bad eating habits among individuals. Some disturbance in the functioning of the liver may cause liver sickness. Liver is responsible for overall functioning of the body. Hence, it becomes necessary to diagnosis the liver disease at an early stage. In advanced world of technology, various methods has been been developed to diagnosis and detect the disease includes data mining. This is novel concept to determine the data by extracting features and recognize indications of liver disease by medical experts. The existing technique has implemented optimize the rules released from Boosted classification with a genetic algorithm, to enhance the LDD (Liver Disease Diagnosis) interval of time and accuracy level. Hence, GA is utilized for enhancing and enhancing directions of another method. In this research work, defines a novel method ECNN (Enhanced CNN) of LDD and enable medical specialists to recognize sign of disease and optimization is done for maximum period, decrease the death rate. Clustering and Feature extraction phase to extract the unique feature based on Kernel method and divide the data into a group or cluster-based using FCM algorithm. Implement CNN method to predict or detect the liver disease to improve the performance and classification of rules set. The proposed method has implemented to achieve better performance and compared with existing methods. The simulation tool used in this research works MATLAB 2016a and calculates the performance is Accuracy achieved 96 % ad existing GA accuracy rate 92.9 % achieved in our work.

BackgroundRefugees often face psychosocial complexity and multi-dimensional healthcare needs. Community-Based Participatory Research (CBPR) methods have been previously employed in designing health programs for refugee communities and in building strong research partnerships in refugee communities. However, the extent to which these communities are involved remains unknown.ObjectiveTo review the evidence on the involvement of refugees in CBPR processes to inform healthcare research.MethodsA scoping review was performed, using Arksey & O’Malley’s methodological framework. A literature search in Medline, PubMed, PsycINFO, CINAHL, Embase, Global Health, Scopus, and Policy File Index for articles published until August 2020 was conducted. Articles were included if they focused on CBPR, had refugee involvement, and discussed healthcare/health policy.Results4125 articles were identified in the database searches. After removal of duplicates, 2077 articles underwent title and abstract review by two authors, yielding an inter-reviewer kappa-statistic of 0.85. 14 studies were included in the final analysis. The purpose of CBPR use for 6 (42.9%) of the articles was developing and implementing mental health/social support interventions, 5 (35.7%) focused on sexual and reproductive health interventions, 1 (7.1%) focused on domestic violence interventions, 1 (7.1%) focused on cardiovascular disease prevention and 1 (7.1%) focused on parenting interventions. In terms of refugee involvement in the various stages in the research process, 9 (64.3%) articles reported refugees having a role in the inception of the research, no articles reported including refugees in obtaining funding, all articles included refugees in the design of the research study, 10 (71.4%) articles reported having refugees involved in community engagement/recruitment, 8 (57.1%) articles reported involvement throughout the data collection process, 4 (28.6%) articles reported involvement in data analysis, 6 (42.9%) articles reported having refugees involved in knowledge translation/dissemination and 1 article (7.1%) reported having refugees contribute to scale up initiatives.ConclusionsCBPR has been identified as a methodology with the potential to make substantial contributions to improving health and well-being in traditionally disenfranchised populations. As the needs of refugee communities are so diverse, efforts should be made to include refugees as partners in all stages of the research process.

METHODS: In a pilot randomized waitlist-controlled trial (Ontario, Canada), individuals aged ≥18 years with Edinburgh Postnatal Depression Scale (EPDS) scores greater than 9 and who self-identified as a mother to a child aged 0-12 months were randomized 1:1 to Mother Matters (intervention) or usual care (control), with an opportunity to receive the intervention after the study was complete. The primary outcome was protocol feasibility, evaluated through recruitment feasibility, intervention acceptability, and adherence to study follow-up measures. Secondarily, postintervention EPDS scores and remission rates (EPDS

In the current global economy, localization in WSNs becomes a hot topic and it is attracting many researchers towards itself. WSN plays an important role in tracking objects in indoor as well as outdoor environments. The sensor data is useless until the location of the reporting node is unknown. The main aim of localization in wireless sensor networks (WSNs) is to determine the coordinates of target nodes in the sensing field by applying different approaches. This can be done either by the global positioning system (GPS) or any other methods. Usually, in localization methods, anchor nodes (GPS-equipped) broadcast beacon signals in the sensing field to help target nodes to localize themselves. The terms localization accuracy, localized nodes and computing time are mainly responsible for the performance of WSNs. The transmission range and density of anchor nodes directly affect the localization error. In this paper, the author surveys the various localization techniques optimized by nature-inspired algorithms and compares the salp swarm optimization algorithm with some well-known existing algorithms.

Wireless communication technologies are increasingly growing in today’s era, which are providing great research opportunities in the networking area. Wireless sensor network (WSN) is one such example of wireless communication technology. WSNs are widely used in agricultural field in order to help farmers cut down their expenses and increase the profit margin. Precision agriculture (PA) is a management strategy that helps to improve the quality as well as the quantity of the production. In this paper, sensor networks are classified on the basis of different parameters, the various issues and the challenges that are faced while deploying WSNs are also reviewed for improved farming. In this review paper, the comparison of different wireless communication protocols and energy-efficient protocols is analyzed comprehensively.

Wireless sensor networks are catching the attention of the researchers in various fields like structural, healthcare monitoring, but the real world adoption is getting difficult due to its dependence on the battery power, so energy harvesting comes to its rescue. To utilize the harvested energy in the best manner, MAC protocols which control the transreceiver in a node are presented here. They are different from the battery powered WSN where the focus is on increasing the lifetime of the nodes, rather these protocols focus on improving the quality of the network. With optimal tradeoff between the infinite network lifetime and energy availability, MAC protocols need to be redesigned for energy harvesting based wireless sensor networks (EHWSN). In this paper first EH technology in wireless sensor networks is discussed. Then a survey of EH based MAC protocols is done in a classified manner. The comparison of the protocols is done based on the different metrics such as energy conservation factor, scalability, latency etc. State of the art literature survey is presented so that users have consolidated data to pick up the one based on their application requirement. Challenges specific to applications is presented along with the various gaps to give an insight into the future research directions. To the best of the author’s knowledge, review of all the EHWSN MAC protocols is not reported till date.

This paper presents a survey on the MAC and network layer of Wireless Sensor Networks. Performance requirements of the MAC layer are explored. MAC layer protocols for battery-powered networks and energy harvesting-based networks are discussed and compared. A detailed discussion on design constraints and classification of routing protocols is presented. Several routing protocols are compared in terms of such parameters as: energy consumption, scalability, network lifetime and mobility. Problems that require future research are presented. The cross-layer approach for WSNs is also surveyed.

Free space optics (FSO) is a capable key which offers high data rate, more secure and cost effective system to other conventional communication systems. Although it is a first and last mile preference to other setups but still lags in a variety of scenarios. The main limitation of FSO is seen in worse weather conditions where it suffers highest attenuation in transmitted signal. The weather which affects the transmission most are rain and haze due to which the received signal fades away and the signal to noise ratio diminishes which violates the characteristics of an ideal FSO link system. In this paper, wavelength division multiplexing (WDM) is used to enhance the signal power with the use of optical amplifiers so that a better signal could be obtained at the receiver. A WDM-FSO system using hybrid configurations of optical amplifiers is proposed which provides a promising solution for low cost and highly efficient systems.

Free space optics has revolutionized the telecom industry through its exquisite data transfer capability and cost effectiveness. It proves out to be an excellent solution to the last mile problem and arduous digging of grounds for laying fiber optic cables. But atmospheric turbulences and obscure weather conditions limit the extensive use of this technology. This paper analyses the use of multibeam technology in enduring the effect of hazy weather on the FSO link by comparing it with the single beam technology. The results obtained from the multibeam system for clear and hazy weather conditions have been validated by using MATLAB codes.

Microbes influence almost every process of life in one or the other way. We have been employing various techniques to study microbial communities and the ways they interact with the environment. With advances in molecular biology, we are now able to study microbes which were unculturable a few decades ago. The study of microbial communities by sequencing DNA samples from various ecological niches is called metagenomics. Parallel advancements in whole-genome sequencing (WGS) technologies have enabled the scientific community to explore complex biological samples cost-effectively. Generation of billions of reads in a single NGS run poses a significant challenge to store, manage and analyze this vast data. Development of novel bioinformatics applications, specifically for metagenomics data, is therefore vital to assign biological significance to metagenomics data. Many strategies have been introduced to deal with quality control, assembly, binning and functional annotation of metagenomic data. However, there is a great scope of improvement in terms of the diversity, uneven representation, variability and scale of data. Nowadays, the focus has also been shifted to integrate various software tools in a logical manner to develop dedicated pipelines built on easy to use graphic-rich interface. So, continuous improvement in computational resources, as well as bioinformatics software applications, is required in order to capture real information from the mammoth of data being generated in metagenome sequencing experiments.

The Internet of things (IoT) covers the whole world, and our myriad daily devices are connected with their surrounding environment in order to collect information to perform specific tasks. These IoT devices need to interact and synchronize with each other, and every place is sensing enabled by a wireless sensor network. The server–client model makes managing the communication and synchronization of a few devices easy. However, if there are thousands of devices, during synchronization the IoT suffers from several limitations and issues, which are most challenging due to its complex environment. To overcome these limitations and issues, blockchain can be used to control and configure IoT devices. Blockchain’s original use was for bitcoin (cryptocurrency), but now its use is expanding to many other fields, including the IoT, healthcare, finances, security, and academic and industrial fields. Now that blockchain technology has been realized as the next revolutionary technology, the primary aim of using blockchain in the IoT is to connect things to the Internet in a peer-to-peer manner, and blockchain is the only distributed ledger maintained by a peer-to-peer network where non trusted participations in the network can communicate with each other without a trusted third party. Blockchain capabilities, such as immutability, auditability, transparency, open source, persistency, and anonymity, can solve most architectural shortcoming of the IoT. Among other things, IoT devices require privacy, security, authentication, protection from attacks, affordability, easy deployment, and self-maintenance. The aim of the IoT is to merge both digital and physical worlds into a single ecosystem that makes up a new intelligent era of the Internet.

Of late, a spurt in the general awareness about the biological aspects of nutrition has been witnessed. The changing trend demands for high nutritional value products that can easily and rapidly be produced at large scales in a cost-effective manner. Microalgae constitutes a distinct group of unicellular photosynthetic organisms and a broad variety of eukaryotic algae containing a plethora of beneficial compounds such as carbohydrate, proteins, fatty acids, vitamins, carotenoids, phycobiliproteins, astaxanthin, and lutein. These compounds find application in the production of high-quality nutraceuticals that provide health benefits such as controlling blood pressure, boosting immune system, reducing coronary heart diseases, serving as anticancer agents, and acting as antioxidants. Besides, the benefits of using microalgae are its high productivity on arable and nonarable land, thus posing no threat to the agricultural crop production. Although the nutritional value and its commercialization is still in nascent stage, intense efforts are underway all over the world to explore untapped potential of microalgae that could lead to the solution of several problems through green technologies and open gateway to a multibillion dollar industry. This chapter gives an overview of microalgae and its diversity, nutritional value, and current challenges on its use as nutraceutical product.

With the fast-track growth of IoT (Internet of Things), wireless sensor networks (WSN) has also gained attention. For effective communication among sensor nodes, protocols are being developed rapidly. Simulation is necessary for any network before deployment to check the functionality and detect the potential errors. Earlier recognition of issues can save both resources and time of network designers. Few simulation environments were already available before the development of WSN technology. Later on, a few other simulation environments were developed specifically for WSN. Simulation environments based on programming language C/C++ and MATLAB are reviewed in this paper. This paper also discusses the extensions of simulation environments. The main focus of this paper is to help novice researchers in choosing an appropriate simulation tool that fits their research criterion.

Objectives Barriers to in-person mental health care are common in pregnant and postpartum women with depression. We assessed the feasibility of a trial protocol for evaluating the use of secure, in-home synchronous virtual psychiatric care. Methods In this pilot randomized controlled trial in Toronto, Canada, women aged ≥18 years, pregnant or 0-12 months postpartum, with Edinburgh Postnatal Depression Scale (EPDS) scores >12, were randomized 1:1 to in-person visits only, or to an intervention condition where they were offered the option of video-visits for some or all of their follow-up care. We assessed trial protocol feasibility, and secondarily EPDS score at 12 weeks post-randomization. Results 63 women were randomized (33 intervention, 30 control) of which 87.9% (n = 29) in the intervention group and 66.7% (n = 20) in control group completed the 12-week follow-up questionnaire. About 48.5% (n = 16) of intervention group participants used video-visits at least once, with high acceptability for participants and providers across a number of domains, and no adverse events. EPDS mean scores decreased from 16.6(SD 5.06) to 11.6(SD 4.77) and 16.9(SD 3.15) to 12.4(SD 3.96) for intervention and control groups, respectively (adjusted mean difference -0.64, 95%CI -2.95 to 1.67). Conclusion It was feasible to recruit for a protocol evaluating psychiatrist video-visits for perinatal depression. Video-visits were acceptable to users and the psychiatrists providing their healthcare. A future non-inferiority efficacy trial can assess treatment outcome moderators to explore variability in effectiveness by illness severity and other factors, and cost-effectiveness of various types of video-visit strategies for psychiatric care in this population.

Traditional Wireless sensor networks rely on a limited energy source, mostly batteries. But most applications need nodes to be an autonomous and continuous operation for months or years. Power consumption by sensor node is the most important part of WSN. MAC protocols help in reduction of power consumption which increases the node lifetime. But it can extend the lifetime to a certain point only, finally, we have to replace the battery. Energy harvesting along with the duty cycling come to the rescue, but now the MAC layer needs to be redesigned. In battery-based WSN the major emphasis is on lifetime only but Green Energy harvesting based protocol focus on effective energy utilization and improving the quality of the network. In this paper, new MAC protocol is designed known as Hybrid multilayer receiver initiated MAC protocol customized for the solar energy.

The unattended nature of the WSN makes the nodes susceptible to various attacks. Among many of the possible attacks, ones that are focused on draining nodes’ energy are most dangerous since they leave the network dead. This paper proposes a scheme to detect the aggressive behavior of nodes by using the packet- forwarding behavior of the nodes. Trust value is lessened if in any case there is a difference between the number of packets forwarded by the sensor hub during data transmission is discovered abnormal. In this way, after a certain number of rounds, nodes which are acting as aggressive will be removed. For transmitting the information over the system effectively when the abnormal hub is to be expelled from existing path would require second way promptly accessible, to take care of this issue in this method two nearest neighboring hubs are chosen to shape two ways. The rendition of the system is analyzed on the basis of remaining energy, packet forwarding ratio, and throughput.

A wireless sensor network is the combination of large numbers of nodes connected to each other in order to communicate with other networks over a particular territory. Within the sensor networks there are two types of attacks which are active and passive attacks. The selective forwarding is the active type of attack in which malicious nodes drop some packets in the network which affect network performance which is considered in this paper. In this research work, technique of threshold is designed which detect and isolate malicious nodes from the network. The simulation results shows improvement in terms of dead nodes, throughput and packet loss.

The area of energy harvesting using vibration sources has attracted numerous researchers over the past few years. It has a great potential to have extended lifetime of low-power devices such as wireless sensors, portable devices, and wearable devices. The wireless devices in today’s date require batteries which have a limited lifetime and needs to be replaced with time. In case of wireless sensors that work in harsh environment, it is nearly impossible to replace batteries. The concept of energy harvesting aims to develop devices that do not require replaceable batteries. This is done by converting available energy from the environment into electrical energy to power wireless devices. This paper is focused on piezoelectric energy harvesting. First, different approaches to harvest energy have been discussed in brief. After that piezoelectric energy harvesting has been discussed in detail. Different components of piezoelectric energy harvesting circuit namely transducers, rectifiers, and storage devices have been discussed.

Since its adoption more than two decades ago in the field of dentistry, three-dimensional (3D) cone-beam computed tomography (CBCT) has rapidly gained popularity as an imaging tool for three-dimensional visualization, diagnosis, and treatment simulation. The objective of this two-part study was to assess landmark identification, as well as the diagnostic value of images obtained using an ultra-low-dose reduced projection (sparse) views algorithm Adaptive-Steepest-Descent-Projection-Onto-Convex-Sets (ASD-POCS) applied to existing dental CBCT data. ASD-POCS was developed for CBCT studies, producing multiple CBCT data files with 12.5% (39), 25% (76), and 50% (150) of the original number of projection views (which is in direct proportion with the lowering of radiation dose). Assessment of 2D landmark identification derived from CBCT data at different projection views was conducted. Assessment of diagnostic quality was studied by evaluating radiographs of various projection views on a visual analog scale by different dental specialists. In conclusion, this study found no statistically significant differences in the quality of images at 25% (76) projection views as compared to 100% (300) projection views. The implementation on ASD-POCS algorithm by the CBCT manufacturers in the future may be beneficial for clinicians in reducing the amount of patient radiation exposure when obtaining routine orthodontic diagnostic radiographs.

A field experiment was conducted during rainy (kharif) and winter (rabi) seasons of 2011-13 to evaluate the effect of application of farmyard manure (FYM), recommended doses of fertilizers (RDF) and their combination on storage protein quality of soybean [Glycine max (L.) Merr.], chickpea (Cicer arietinum L.) and wheat (Triticum aestivum L.) in soybean based cropping system in Punjab. Densitometric analysis of chromatograms revealed significant variations in relative densities of α' subunit of β-conglycinin protein in soybean in year 2011 and α subunit of legumins in chickpea among different treatments whereas other subunits of glycinin and β-conglycinin in soybean and legumins and vicillins in chickpea did not vary significantly. Maximum value of 11S/7S ratio was observed in treatment with FYM @ 10t ha-1 and FYM @ 10t ha-1+100% RDF in soybean seeds in year 2011 and 2012 respectively and with RDF in chickpea. In wheat, the relative quantity of 55.7, 48.8 and between 11-13 kDa bands increased significantly in combined treatment of organic or inorganic fertilizer than their individual treatments, whereas relative quantity of 40.7 kDa band was significantly low in FYM @10t ha-1 +100% RDF treatment as compared to other treatments. Combined treatments of organic and inorganic fertilizer resulted in presence of additional bands corresponding to 61.4 and 22.5 kDa and disappearance of subunit band corresponding to 16.4 kDa in wheat grains. It is concluded that combined organic and inorganic treatments did not change major storage protein fractions and can be used to improve fertilizer management practices.

In this paper, the optical character recognition is used to recognize the scanned English documents by using neural network and MDA. The human mind easily read any interrupted scanned documents but it is difficult to machine. So the optical character recognition are solved this problem. The output images are not editable by capturing camera or scanned document but with the help of optical character recognition this problem easily solved. The OCR process consists of three major sub processes like pre processing, segmentation and recognition. The neural networks are playing very important role for character recognition its helps to provide high accuracy for the character.

Optical character recognition (OCR) is more popular system for research field. In India, a lot of work has been done on various scripts, like Devanagari, Bangla, Tamil, Gujarati, Oriya etc. In this paper, we present a review of various OCR systems for Gurmukhi scripts. All the feature extraction techniques for extracting the features, classifiers for classification are discussed in various section of this paper. At the end, we have concluded various techniques on the basis of their accuracy.

Wireless sensors collect the data and transmit it to the base station through a network of nodes. The flow of data through the network can also be termed as traffic flow. The nature of traffic flow in a network depends upon application for which network is designed. Modeling traffic flow for a wireless sensor network (WSN) is as important as designing the MAC or routing protocol. In fact, estimating the flow of expected traffic is a prerequisite of designing a protocol. Efficient estimation of traffic flow helps in determining resource requirements. Overestimation and underestimation of the traffic pattern and flow can lead to wastage or exhaustion of resources. Medium access control (MAC) protocol is responsible for shared access of media among nodes. Poisson distribution is used for shaping of traffic for multilayer MAC (ML-MAC). This paper proposes another traffic profiles such as Pareto and generalized Pareto distribution (GPD) for ML-MAC which are more realistic than Poisson. Further, it simulates ML-MAC for the proposed traffic models. Finally, this paper compares the results in terms of energy consumption and average delay. The results are further justified and concluded by providing supporting applications.

Radio over fiber (RoF) is one of the primary technologies for the provision of future broadband networks. This work is focused to the implementation of cost effective radio over multimode system (Ro-MMF) for long haul communication. A 10 Gbps data along with 10 GHz radio signal is transmitted over multimode fiber link of 40 km. Moreover, the results are also reported for proposed Ro-MMF system by using LG 00, LG 01 & LG 02 modes.

Primary cardiac tumors are rare and usually benign. The incidence of cardiac lipomas is 8 % of benign cardiac tumors [1]. Several surgical options have been reported to obtain an appropriate operative view because of their poor visualization when the tumors are located in the Left Ventricle (LV). We report a rare case of massive left ventricular lipoma occupying pericardial space. A 23-year-old female had back pain since 6 months. She visited a local orthopedician, who ordered for computed tomography scan of chest and back. Computed tomography showed a large epicardial mass located along the anterior surface of the heart, from the diaphragm level through the aortic arch level. The mass showed an attenuation value identical with that of subcutaneous adipose tissue and contained some areas with high density. The mass was not enhanced by contrast media. Percutaneous biopsy was done, histologic examination of the specimen demonstrated mature adipose tissue. An encapsulated adipose mass weighing 865 g, which originated from the left ventricle anteriorolateral surface without any invasion to the pericardium, was near completely excised, except for a small portion which was encasing obtuse marginal artery. Microscopic examination revealed mature adipose tissue with partial necrosis, confirming the diagnosis of lipoma.

Purpose of review This review examines associations between fibroblast growth factor 23 (FGF-23) and cardiovascular disease. Recent findings FGF-23 is a hormone produced by osteocytes and osteoblasts that aids with phosphate excretion by the kidney and acts as a negative feedback regulator for activated vitamin D synthesis. Recent studies have found associations between elevated FGF-23 levels and a number of cardiovascular diseases, including hypertension, left ventricular hypertrophy, endothelial dysfunction, cardiovascular events and mortality. Conclusion Recent studies have explored the possible effects of FGF-23 on the cardiovascular system. In animal and observational human studies, there is a link between elevated FGF-23 levels and multiple cardiovascular outcomes, including hypertension, left ventricular hypertrophy and cardiovascular events and mortality. Further studies are required to evaluate whether decreasing FGF-23 levels improves cardiovascular outcomes.

There is a tremendous growth in telecommunication networks due to the emergence of various communication techniques. Optical communications have been the major contributors to it. Free space optical communication (FSO) is a technique based on transmission of data by propagating the light in free space. This is an effective technique to transmit the data at high bit rate over short distance with the added advantage of easy and fast installation and high security. Hybrid RF/FSO technique improve the overall reliability of the system. In this paper, aerial application of the RF/FSO system, i.e., airborne Internet which includes the use of optical links in the network of unmanned aerial vehicles (UAVs) is given. Different formations of UAV swarms, few methods to combat the problems faced by unmanned aerial vehicles (UAVs) and high altitude platform (HAPs) for research work have been discussed. A model is also proposed to improve the reliability of the swarm network.

Cloud Computing is a vast paradigm to operate on remote devices using which one can access any data, platform or any kind of infrastructure.In this paper we have done a survey on the context aware framework that is used in the smart cities. In this paper CAMELO framework is studied along with the advantages and ease of use in it. A context-aware service discovery framework based on mobile cloud computing environment is reviewed in this paper.

The need to control the short channel effects in transistor that occurs in nanometer regime has caused the invention of multi gate transistors over planar bulk transistors in order to improve the performance. In this research paper the 3D model of SOI FinFET and Bulk MOSFET at 20nm node technology is designed and their transfer characteristics, drain characteristics and short channel effects are reported. The OFF state leakage current, DIBL, and threshold voltage of SOI FinFET and bulk MOSFET has been calculated. The simulation is performed using TCAD simulator. The simulation results has shown that the OFF state leakage current is less in FinFET as compared to bulk MOSFET and the Ion in SOI FinFET is higher than that of bulk MOSFET. The DIBL of bulk MOSFET is found to be 2.57 times more than that of SOI FINFET, so SOI FinFET has shown reduction in short channel effects as compared to bulk MOSFET at 20nm gate length. GIDL is also examined in both devices. The drain current of SOI FinFET at Vgs= 0.1V is observed higher than that of bulk MOSFET.

Pulmonary embolectomy in the treatment of massive pulmonary embolus has been in doubt since the introduction of thrombolytic therapy. Recent indications for surgical intervention are- contraindication to thrombolysis, failed medical treatment and severe Right Ventricular (RV) dysfunction. A 54-year male came to us with complaints of palpitation, tachypnea and repeated syncope . Transthoracic echocardiography and Computed Tomography pulmonary angiogram demonstrated- Biatrial mass with right atrial mass extending into right ventricle and main pulmonary artery. Pulmonary embolectomy was performed. Residual emboli of bilateral pulmonary arteries were detected with a fiberoptic pediatric bronchoscope and removed. Bronchoscopic evaluation appears to be safe and useful for direct visual detection of emboli.

Agricultural sector can be rightly called upon as the mother and the caretaker of all the major and minor sectors. The rural agrobased industries were the effective means to absorb rural population that was either unemployed or under-employed. To study the socio-economic profile of entrepreneurs engaged in gur khandsari as agro-based village industries and to analyze the economics of gur khandsari enterprise, the study was conducted in Fatehgarh district of Punjab state. From 40 villages falling in the districts, 15 entrepreneurs of gur khandsari enterprise were found. These were categorized into different farm categories according to their agricultural land ownership. The study revealed that all the entrepreneurs were male and their average age was 44.33 year. Average agricultural land ownership of 15 entrepreneurs was 6.83 acres and average limit of credit was 3.39 lakh. Capital investment was highest for entrepreneurs who had small farms (293700). Annual net returns were found highest (112492) in the case of semimedium farm entrepreneurs. By investing one rupee on fixed and variable resources of gur khandsari enterprise, earned an amount of 1.27 on an average in Punjab as is indicated by the output-capital ratio in gur khandsari. This shows that there were net earnings of rupee 0.18 which came to be 16.69 percent of total earning and remaining 83.31 percent was the total cost on an average of Punjab. Similarly, benefit cost ratio at both variables and fixed costs were 0.27 and 0.18 respectively. The average payback period of gur khandsari enterprise was 2.13 year.

Multipliers are the key block in high speed arithmetic logic units, multiplier and accumulate units, digital signal processing units etc. With the increasing constraints on delay, more and more emphasis is being laid on design of faster multiplications. To enhance speed many modifications over the standard modified booth algorithm, Wallace tree methods for multiplier design have been made and several new techniques are being worked upon. Amongst these Vedic multipliers based on Vedic mathematics are presently under focus due to these being one of the fastest and low power multiplier. There are sixteen sutras in Vedic multiplication in which “Urdhva Tiryakbhyam” has been noticed to be the most efficient one in terms of speed. A large number of high speed Vedic multipliers have been proposed with Urdhva Tiryakbhyam sutra. Few of them are presented in this paper giving an insight into their methodology, merits and demerits. Compressor based Vedic Multipliers show considerable improvements in speed and area efficiency over the conventional ones.

Studies were conducted on the effect of photoperiodic treatments on regulation of flower production in two standard varieties of chrysanthemum viz. Thai Ching queen and Purnima. The plants raised through rooting of terminal cuttings were maintained under long day (LD) condition from 15 August to 15 February by interrupting the night period daily for two hours from 10 pm to 12 am by placing the pots under CFL lamps (23 Watt). These plants were periodically shifted to natural day length (ND) condition from September to February. Time of flower production in both the varieties was significantly affected by photoperiod treatments. Transferring plants from ND to natural short day length (SD) condition in September and October decreased number of days to produce flowers as compared to those maintained continuously under ND condition w.e.f. August. The plants transferred from LD to ND condition in the month of November and December took longer to reach commercial flower harvesting stage where as those transferred to ND condition in the months of January and February produced flowers in minimum number of days, respectively. Flower production in two varieties under study could be extended to end of April but the post harvest quality of flowers produced decreased due to rise in temperature in March and April.

A In software development organizations, Component based Software engineering (CBSE) is emerging paradigm for software development and gained wide acceptance as it often results in increase quality of software product within development time and budget. In component reusability, main challenges are the right component identification from large repositories at right time. The major objective of this work is to provide efficient algorithm for storage and effective retrieval of components using neural network and parameters based on user choice through clustering. This research paper aims to propose an algorithm that provides error free and automatic process (for retrieval of the components) while reuse of the component. In this algorithm, keywords (or components) are extracted from software document, after by applying k mean clustering algorithm. Then weights assigned to those keywords based on their frequency and after assigning weights, ANN predicts whether correct weight is assigned to keywords (or components) or not, otherwise it back propagates in to initial step (re-assign the weights). In last, store those all keywords into Repositories for effective retrieval. Proposed algorithm is very effective in the error correction and detection with user base choice while choice of component for reusability for efficient retrieval is there. To check the results of our algorithm based on factors like accuracy, precision and recall compare with existing technique i.e. integrated classification scheme for retrieval of components based on keyword search and results are so encouraging.

Free Space Optical communication (FSO) has engrossed a large section of researchers in recent times due to its wide bandwidth, effortless deployment and immune links making it appropriate for communication purposes. This wireless optical technique requires clear and non-turbulent atmospheric conditions for efficient transmission. In this paper, authors aim at reducing the effect of turbulent atmospheric conditions like scintillation effect on FSO. Multibeam technique, which uses spatially diverse transmitters for transmission, has been used for increasing the achievable link distance of the FSO system. Parameters like quality factor and bit error rate have been used to check the received signal quality.