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In order to provide benchmark performance for Urdu text document classification, the contribution of this paper is manifold. First, it provides a publicly available benchmark dataset manually tagged against 6 classes. Second, it investigates the performance impact of traditional machine learning-based Urdu text document classification methodologies by embedding 10 filter-based feature selection algorithms which have been widely used for other languages. Third, for the very first time, it assesses the performance of various deep learning-based methodologies for Urdu text document classification. In this regard, for experimentation, we adapt 10 deep learning classification methodologies which have produced best performance figures for English text classification. Fourth, it also investigates the performance impact of transfer learning by utilizing Bidirectional Encoder Representations from Transformers approach for Urdu language. Fifth, it evaluates the integrity of a hybrid approach which combines traditional machine learning-based feature engineering and deep learning-based automated feature engineering. Experimental results show that feature selection approach named as normalized difference measure along with support vector machine outshines state-of-the-art performance on two closed source benchmark datasets CLE Urdu Digest 1000k, and CLE Urdu Digest 1Million with a significant margin of 32% and 13%, respectively. Across all three datasets, normalized difference measure outperforms other filter-based feature selection algorithms as it significantly uplifts the performance of all adopted machine learning, deep learning, and hybrid approaches. The source code and presented dataset are available at Github repository https://github.com/minixain/Urdu-Text-Classification .

In order to accelerate the performance of various Natural Language Processing tasks for Roman Urdu, this article for the very first time provides 3 neural word embeddings prepared using most widely used approaches namely Word2vec, FastText, and Glove. The integrity of generated neural word embeddings is evaluated using intrinsic and extrinsic evaluation approaches. Considering the lack of publicly available benchmark datasets, it provides a first-ever Roman Urdu public dataset which consists of 3241 sentiments annotated against positive, negative, and neutral classes. To provide benchmark baseline performance over the presented dataset for Roman Urdu sentiment analysis, we adapt diverse machine learning (Support Vector Machine, Logistic Regression, Naive Bayes), deep learning (convolutional neural network, recurrent neural network), and hybrid deep learning approaches. Performance impact of generated neural word embeddings based representation is compared with other most widely used bag of words based feature representation approaches using diverse machine and deep learning classifiers. In order to improve the performance of Roman Urdu sentiment analysis, it proposes a novel precisely extreme multi-channel hybrid methodology which makes use of convolutional and recurrent neural networks along with pre-trained neural word embeddings. The proposed hybrid approach outperforms adapted machine learning approaches by the significant figure of 9% and deep learning approaches by the figure of 4% in terms of F1-score.

Zinc telluride thin films can be used in a large variety of applications such as optoelectronics and microelectronics tools. In this paper, the growth of ZnTe films prepared by electrodeposition, thermal evaporation and closed space sublimation method with various precursors and some its physical properties of obtained zinc telluride films are discussed.

The evolution of Internet of Things (IoT) has increased the appetite for the energy efficient wireless infrastructures. Most of the IoT devices are inherently resource constrained and heterogeneous in respect of their traffic demand. Moreover, these devices need to be made adaptable to the varying environmental conditions. However, existing traffic scheduling and duty cycling algorithms lack the capability to meet the dynamic service quality requirements of IoT applications with variable context information. Specifically, they are infeasible for IoT use-cases where multi-hop communication is required. This paper strives to realize efficient resource allocation to the Wi-Fi based IoT devices in multi-hop IoT infrastructures. Firstly, IoT applications are characterized as per their heterogeneous traffic demand and mapped to the distinct weighted quality classes. Then, context awareness is introduced for IoT devices and an optimization model constrained by their service quality requirements and context priorities is presented. Further, an energy efficient context aware traffic scheduling (EE-CATS) algorithm is proposed wherein the convergence of model is specified by a sub-gradient projection method. The EE-CATS algorithm efficiently allocates resources to multi-hop IoT devices and reduce their total awake time by employing adaptive duty cycling. The performance evaluation is done for various IoT use-cases through simulations in Network Simulator (ns-2) and testbed implementation in Contiki operating system. The results suggest substantial improvements in the energy efficiency of IoT devices while ensuring their dynamic service requirements. In addition, the proposed algorithm minimizes the end-to-end delays in overall IoT networks.

Background Arteriovenous fistula (AVF) formation is the most common vascular access procedure for patients requiring haemodialysis. However, it is associated with high failure rates, influenced by vessel diameter and arterial inflow. Mode of anaesthesia may affect these factors, and subsequently AVF maturation rates. Objective To perform a systematic review and meta-analysis to assess the effect of anaesthesia type for autologous primary radiocephalic or brachiocephalic AVF creation on subsequent fistula failure rates. Methods The online databases of Medline, EMBASE, CINAHL, The Cochrane Database of Systematic Reviews, ClinicalTrials.gov , and Google Scholar as well as vascular and anaesthesiology conference abstracts were searched on August 1, 2016. Randomised control trials (RCTs) that reported the effect of anaesthesia type on subsequent failure rates during autologous AVF creation were included. Two independent reviewers performed methodological assessment and data extraction. Random effects models were used to calculate pooled effect size estimates. A sensitivity analysis was also carried out. Results Four RCTs (286 patients) were identified with 286 autologous AVFs. There were 48 fistula failures. Most of the studies suffered from significant methodological flaws. There was a significantly lower failure rate among patients undergoing regional (12/143) compared with local (36/143) anaesthesia (OR 0.28, 95% CI 0.14–0.57). On sensitivity analysis, having excluded the most heavily weighted study, the results remained significant (OR 0.20, 95% CI 0.05–0.75). Conclusions The use of regional anaesthesia is associated with lower AVF failure rates when compared with local anaesthesia in patients undergoing primary forearm AVF formation for haemodialysis.

Stabilized un-doped Zinc Telluride (ZnTe) thin films were grown on glass substrates under vacuum using closed space sublimation (CSS) technique. A dilute copper nitrate solution (0.1/100 ml) was prepared for copper doping known as ion exchange process in the matrix of ZnTe thin film. The reproducible polycrystalline cubic structure of undoped and Cu doped ZnTe thin films with preferred orientation (111) was confirmed by X-rays diffraction (XRD) technique. Lattice parameter analyses verified the expansion of unit cell volume after incorporation of Cu species into ZnTe thin films samples. The micrographs of scanning electron microscopy (SEM) were used to measure the variation in crystal sizes of samples. The energy dispersive X-rays was used to validate the elemental composition of undoped and Cu-doped ZnTe thin films. The bandgap energy 2.24 eV of ZnTe thin film decreased after doping Cu to 2.20 eV may be due to the introduction of acceptors states near to valance band. Optical studies showed that refractive index was measured from 2.18 to 3.24 whereas thicknesses varied between 220 nm to 320 nm for un-doped and Cu doped ZnTe thin film respectively using Swanepoel model. The oxidation states of Zn+2, Te+2 and Cu+1 through high resolution X-ray photoelectron spectroscopy (XPS) analyses was observed. The resistivity of thin films changed from ~107 Ω-cm for undoped ZnTe to ~1 Ω-cm for Cu-doped ZnTe thin film, whereas p-type carrier concentration increased from to respectively. These results predicted that Cu-doped ZnTe thin film can be used as an ideal, efficient and stable intermediate layer between metallic and absorber back contact for the heterojunction thin film solar cell technology.

ObjectivesTo use high-resolution imaging to characterise palindromic rheumatism (PR) and to compare the imaging pattern observed to that seen in new-onset rheumatoid arthritis (NORA).MethodsUltrasound (US) assessment of synovitis, tenosynovitis and non-synovial extracapsular inflammation (ECI) was performed during and between flares in a prospective treatment-naive PR cohort. MRI of the flaring region was performed where possible. For comparison, the same US assessment was also performed in anticyclic citrullinated peptide (CCP) positive individuals with musculoskeletal symptoms (CCP+ at risk) and patients with NORA.ResultsThirty-one of 79 patients with PR recruited were assessed during a flare. A high frequency of ECI was identified on US; 19/31 (61%) of patients had ECI including 12/19 (63%) in whom ECI was identified in the absence of synovitis. Only 7/31 (23%) patients with PR had synovitis (greyscale ≥1 and power Doppler ≥1) during flare. In the hands/wrists, ECI was more prevalent in PR compared with NORA and CCP+ at risk (65% vs 29 % vs 6%, pConclusionPR has a distinct US pattern characterised by reversible ECI, often without synovitis. In patients presenting with new joint swelling, US may refine management by distinguishing relapsing from persistent arthritis.

Exponential growth of biomedical literature and clinical data demands more robust yet precise computational methodologies to extract useful insights from biomedical literature and to perform accurate assignment of disease-specific codes. Such approaches can largely enhance the effectiveness of diverse biomedicine and bioinformatics applications. State-of-the-art computational biomedical text classification methodologies either solely leverage discrimintaive features extracted through convolution operations performed by deep convolutional neural network or contextual information extracted by recurrent neural network. However, none of the methodology takes advantage of both convolutional and recurrent neural networks. Further, existing methodologies lack to produce decent performance for the classification of different genre biomedical text such as biomedical literature or clinical notes. We, for the very first time, present a generic deep learning based hybrid multi-label classification methodology namely GHS-NET which can be utilized to accurately classify biomedical text of diverse genre. GHS-NET makes use of convolutional neural network to extract most discriminative features and bi-directional Long Short-Term Memory to acquire contextual information. GHS-NET effectiveness is evaluated for extreme multi-label biomedical literature classification and assignment of ICD-9 codes to clinical notes. For the task of extreme multi-label biomedical literature classification, performance comparison of GHS-Net and state-of-the-art deep learning based methodology reveals that GHS-Net marks the increment of 1%, 6%, and 1% for hallmarks of cancer dataset, 10%, 16%, and 11% for chemical exposure dataset in terms of precision, recall, and F1-score. For the task of clinical notes classification, GHS-Net outperforms previous best deep learning based methodology over Medical Information Mart for Intensive Care dataset (MIMIC-III) by the significant margin of 6%, 8% in terms of recall and F1-score. GHS-NET is available as a web service at1 and potentially can be used to accurately classify multi-variate disease and chemical exposure specific text.

Functional magnetic resonance imaging (fMRI) data analysis is developing rapidly in a fast emerging society, because of temporal and spatial resolution and the inoffensive feature of their acquisition in human brains. Spatial resolution governs how “sharp” the image is in appearance, whereas temporal resolution denotes the precision of a measurement with respect to time. The goal of fMRI technique is to identify the activation pattern and functional connectivity in the brain regions. In our study, artificial neural network technique was used for the identification and classification of decision-making voxels of fMRI data based on Brodmann areas 10 and 47 from the prefrontal cortex of human brain. The total number of voxels of Brodmann areas was 159, and we determined that some particular voxels played dominant role for decision-making process while performing a visual task. We also analyzed true positive and false positive classification rates between two decisions in the context of a well-known receiver operating characteristic curve (ROC).

The successful use of intelligent agents in healthcare has attracted researchers to apply this emerging software engineering paradigm in more advanced and complex applications. Main success factor is the natural mapping of real world medical problems into cyber world. Multi-agent architecture can easily model the heterogeneous, distributed and autonomous health care systems. The multi agent systems have been applied from single healthcare activity like knowledge based medical system to complex, multi-component based systems like complete healthcare unit. The use of multi agent systems in health care domain has also opened the ways to find out new applications like personalized and socialized health care systems. This versatile use of multi agent systems has also posed new problems for researchers like; security, communication, and different social issues. This work reviews recent years' research and applications of multi agent systems in healthcare published in different research journals, international conferences, and implemented practically. We reviewed five subdomains and three systems in each subdomain. A set of common parameters of these systems has been extracted and compared to analyze systems' merits and deficiencies. Based on our analysis, we have provided recommendations for multi agent systems applied in healthcare domain. Future research directions for interested researchers and practitioners are also discussed. As our own future research work, we intend to study healthcare and multi agent systems in e-commerce.

The article [Benchmarking performance of machine and deep learning-based methodologies for Urdu text document classification], written by [Muhammad Nabeel Asim, Muhammad Usman Ghani, Muhammad Ali Ibrahim, Waqar Mahmood, Andreas Dengel and Sheraz Ahmed], was originally published.

Pakistan has a key problem of power supply in urban as well as rural areas having very limited supply of electricity. Being an agricultural country, Pakistan produces a significant volume of agro-waste having little economic use at the moment. The increased consciousness in green house emission has motivated to develop new technologies to accommodate the detention and confiscation of CO 2 . Keeping in mind the scenario, the combustion and pyrolysis behavior of Pakistani lignite (PL), rice husk (RH) and their blends of PL50/RH50 wt.%, PL40/RH60 wt.% and PL30/RH70 wt.% were examined in oxy-fuel and nitrogen environments for their probable use as sustainable and alternative energy resource. Combustion profiles of rice husk and lignite blends lie between those of individual fuels. Thermal stability of the lignite was observed to be decreased as increase of rice husk and suggest favoring when more energy is needed in short interval of time. Energy potential of PL50/RH50 blend was better due to the presence of higher amount of carbon and calorific value, low amount of ash and sulfur contents. Activation energy found to be decreased with the increase of rice husk quantity in pyrolysis reaction and associated with carbon content of lignite. The reduction in activation energy indicated the decrease in the operational temperature and suggests that gasification process will start at lower temperature for blends of lignite and rice husk than individual lignite.

Question classification is considered one of the most significant phases of a typical Question Answering (QA) system. It assigns certain answer types to each question which leads to narrow down the search space of possible answers for factoid and list type questions. The process of assigning certain answer types to each question is also known as Lexical Answer Type (LAT) Prediction. Although much work has been done to enhance the performance of question classification into coarse and fine classes in diverse domains, it is still considered a challenging task in the biomedical field. The difficulty in biomedical question classification stems from the fact that one question might have more than one label or expected answer types associated with it (also, referred to as a multi-label classification). In the biomedical domain, only preliminary work is done to classify multi-label questions by transforming them into a single label through copy transformation technique. In this paper, we have generated a multi-labeled corpus (MLBioMedLAT) by exploring the process of Open Advancement of Question Answering (OAQA) system for the task of biomedical question classification. We use 780 biomedical questions from BioASQ challenge and assign them appropriate labels. To annotate these labels, we use the answers for each question and assign the question semantic type labels by leveraging an existing corpus and utilizing OAQA system. The paper introduces a data transformation approach namely Label Power Set with logistic regression (LPLR) for the task of multi-label biomedical question classification and compares its performance with Structured SVM (SSVM), Restricted Boltzmann Machine (RBM), and copy transformation based logistic regression (CLR) (previously used for a similar task in the OAQA system). To evaluate the integrity of the introduced data transformation technique, we use three prominent evaluation measures namely Micro F 1 , Accuracy, and Hamming Loss. Regarding MicroF 1 , our introduced technique coupled with a new feature set surpasses CLR, SSVM, and RBM with a margin of 7%, 8%, and 22% respectively.

Cadmium sulphide (CdS) is the n-type, wide band gap II-VI semiconducting material by offering applications in photovoltaics. Among the range of applications offered by CdS thin films, it has found application as a window layer in second generation solar cells by creating photon traps, thereby quantum efficiency. Closed space sublimation (CSS) offers a trivial yet effective approach for the synthesis of thin films for solar cell applications at moderate temperatures. CdS thin films of controlled thicknesses were synthesized by CSS technique by varying exposure time. X-rays diffraction data of these thin films revealed polycrystalline nature with a preferred orientation along (002) direction. The scanning electron microscopy (SEM) based morphological studies showed grain size variation with an increase in thickness of deposited thin films in the range of 300–500 nm. The electrical studies revealed high resistivity of the order of 106 Ω-cm. Spectrophotometric studies performed for CdS thin films concluded with the calculation of the optical parameters such as refractive index, absorption coefficient employing the Swanepoel model, and energy band gap of ∼2.42 eV using the Tauc relation in addition to thin film thickness confirmation. The variations in thickness affect the structure, surface, optical (Khan et al. 2018), electrical properties.

Biomedical information retrieval systems are becoming popular and complex due to massive amount of ever-growing biomedical literature. Users are unable to construct a precise and accurate query that represents the intended information in a clear manner. Therefore, query is expanded with the terms or features that retrieve more relevant information. Selection of appropriate expansion terms plays key role to improve the performance of retrieval task. We propose document frequency chi-square, a newer version of chi-square in pseudo relevance feedback for term selection. The effects of pre-processing on the performance of information retrieval specifically in biomedical domain are also depicted. On average, the proposed algorithm outperformed state-of-the-art term selection algorithms by 88% at pre-defined test points. Our experiments also conclude that, stemming cause a decrease in overall performance of the pseudo relevance feedback based information retrieval system particularly in biomedical domain. Database URL: http://biodb.sdau.edu.cn/gan/

Brain Computer Interfaces (BCI) are a natural extension to Human Computer Interaction (HCI) technologies. BCI is especially useful for people suffering from diseases, such as Amyotrophic Lateral Sclerosis (ALS) which cause motor disabilities in patients. To evaluate the effectiveness of BCI in different paradigms, the need of benchmark BCI datasets is increasing rapidly. Although, such datasets do exist, a comparative study of such datasets is not available to the best of our knowledge. In this paper, we provided a comprehensive overview of various BCI datasets. We briefly describe the characteristics of these datasets and devise a classification scheme for them. The comparative study provides feature extractors and classifiers used for each dataset. Moreover, potential use-cases for each dataset are also provided.

Cadmium sulfide (CdS) has been investigated extensively for II generation solar cell as an efficient window layer with n type conductivity. The significance of CdS is because of its large energy band gap tune-ability and native n-type conductivity. In this report, energy band gap engineering of CdS films was carried out by means of controlled silver (Ag) doping to modify their optical properties along with electrical properties. Closed space sublimation (CSS) technique has been employed to synthesize as-deposited CdS thin films. One of the advantages of CSS grown films is roughness which offers more trapping/absorbing of light. Ion exchange solution process was carried out for Ag-doping, which resulted in widening of the band gap from 2.15 eV to a value of 2.45 eV, showing the increased capability of solar energy harvesting. Un-doped CdS thin films showed a high resistivity of the order of ∼106 Ω-cm, which reduced to only ∼102 Ω-cm with the Ag-doping, as probed by four-point probe, offering great advantage for the system to be used in II-VI solar cells. Un-doped and Ag-doped films showed n-type conductivity. We studied the Ag-doping effects on the surface morphological and correlated the morphological modification with changing optical and electrical behaviour of CdS thin films. It is believed that enhanced properties offer great potential for these films to be used for the solar cell applications.

Internet of Things (IoT) systems cannot successfully realize the notion of ubiquitous connectivity of everything if they are not capable to truly include 'multimedia things'. However, the current research and development activities in the field do not mandate the features of multimedia objects, thus leaving a gap to benefit from multimedia content based services and applications. In this paper, we analyze this issue by contemplating the concept of IoT and drawing an inspiration towards the perspective vision of 'Internet of Multimedia Things' (IoMT). Therein, we introduce IoMT as a novel paradigm in which smart heterogeneous multimedia things can interact and cooperate with one another and with other things connected to the Internet to facilitate multimedia based services and applications that are globally available to the users. Some applications and use-cases for IoMT are presented to reflect the possibilities enabled by this new paradigm. An IoMT architecture is then presented which is segregated into four distinct stages; (i) multimedia sensing, (ii) reporting and addressability, (iii) multimedia-aware cloud, and (iv) multi-agent systems. Instead of proposing specific technical solutions for each individual stage of the presented architecture, we survey the already existing technologies, providing a synthesis for the realization of the vision of IoMT. Subsequently, various requirements and challenges as well as the feasibility of existing solutions for each stage of proposed IoMT architecture are comprehensively discussed.

Cadmium sulfide (CdS) is a prominent material for its tunable band gap used as a window layer in II–VI semiconductor solar cells. The light trapping capability of window layer is one of the powerful tools to enhance the efficiency of the cell. CdS and zinc (Zn) powders were mixed mechanically with different weight percents to make CdZnS (CZS) powder. CZS was deposited onto an ultrasonically cleaned glass substrate using close spaced sublimation (CSS) technique. CZS as-deposited thin films were characterized for structural, surface morphology with energy dispersive X-rays (EDX) and optical properties for the use of window layer in CdS/CdTe based solar cells. The different Zn concentrations in CZS played a vital role on crystallite size in structural analysis and optical properties e.g. transmission, absorption coefficient and energy band gap, etc. The crystallite size of as-deposited CZS thin films were increased as Zn concentration was increased up to certain value. The energy band gap varies from 2.42 eV to 2.57 eV for as-deposited CZS thin films with increasing Zn concentrations and surface morphology changes also. These changes were occurred due to zinc diffusion in CdS thin films. An angle resolved transmission data was taken to check the behavior of CdS and CZS thin film at different angles. A comparative study was carried out between CdS thin films and CZS thin films for the use of good window layer material.

Zinc telluride (ZnTe) thin films were fabricated by using closed space sublimation (CSS) technique on glass substrate under vacuum. Pre-fabricated ZnTe thin films were doped with silver (Ag) by ion exchange method. X-ray diffraction showed the preferred orientation (111) of ZnTe thin film with polycrystalline behavior. Scanning electron microscope images were taken to estimate the grain boundaries; energy dispersive X-ray results confirmed the Ag composition in doped-ZnTe samples. Electrical measurements were performed to determine the resistivity, mobility and carrier concentrations of un-doped thin films and Ag-doped samples. The electrical resistivity was of the order of 10 6 Ω-cm before doping. Ag-doped ZnTe samples exhibits low resistivity of the order of 10 3 Ω-cm along with a change in the carrier concentrations and mobility as well at room temperature. The angle resolved optical transmission data, taken by spectrophotometer, was used to find the optical properties before and after Ag doping. Energy band gap showed decreasing trend with increasing Ag doping time.

Thin films of cadmium sulfide with very well defined preferential orientation and relatively high absorption coefficient were fabricated by thermal evaporation technique. The research is focused to the fabrication and characterization of the compositional data of CdS thin films obtained by using X-ray diffraction, scanning electron microscope along with energy dispersive X-ray spectroscopy. The optical properties were studied by using a UV-VIS-NIR spectrophotometer. The effects of silver-doping by ion exchange process on the properties of as-deposited CdS thin films have been investigated.

Optical burst switching realizes all-optical communication by dividing data transmission system into control plane and data plane. In order to implement control plane two controlling mechanisms such as distributed and centralized control and reservation models have been presented in literature. Both of the architectures have pros and cons associated such as distributed model lacks efficient resource utilization while centralized model is nonscalable. In order to overcome these, a new hybrid control and reservation mechanism has been presented by the authors. The proposed model is based on clustering technique where each cluster consists of cluster head and member nodes. Cluster head performs major functionalities in the network such as path establishment, routing and resource management, fault management, etc., while member nodes perform data switching functionality. In order to implement the architecture, a signaling protocol is also presented. In this paper, we discuss different scenarios required for the implementation of the proposed hybrid model. These scenarios detail the message dialogs exchange between different network nodes and between different software modules during lightpath establishment, data transmission, and connection teardown operations. The goal of efficient resource utilization is achieved through centralized control of network resources while scalability is achieved through dividing the network into multiple domains. Finally, the simulation section shows the mechanism of designing the multidomain architecture, network bandwidth utilization comparison and reduction in end-to-end data transmission latency.

Energy Deficiency problem can be addressed either by increasing generation or by efficient consumption of energy. Shortage of electricity generation and excessive usage of electricity power has promoted the energy conservation measures. Energy audit of building identifies flaws in load consumption; and overall energy performance profile can be improved. This case study presents the complete energy audit of a Public sector Multi-Office building located in Lahore, Pakistan. A methodical analysis has been performed and potential Energy Conservation Recommendations (ECRs) are proposed for the building. These ECRs are backed up by the financial analysis. Analysis concludes that more than 30% energy can be saved by efficient utilization and retrofitting measures only. On field collected data has been analyzed using software; DIALuxEvo 3 for lighting system, Hourly Analysis Program (HAP4.41) for heating and cooling system and Smart-Viewer for thermal imaging.

This paper introduces a novel model for analyzing the optical interface performance degradation due to scratches on optical fiber end face. The model indicates that the contribution to the return loss (RL) of a scratch is determined by its size, location, and its relative reflectivity, which is defined as the ratio of the average reflectivity of the scratch to the base reflectivity of the defectless end face. Based on this new model, the effects on RL are analyzed for scratches of various numbers, different sizes, with different relative reflectivities, and at different locations. This quantified analysis provides a solid base to establish the specifications of inspection criteria of optical fiber connectors. With the new model, the relative reflectivity of a scratch was tested, and estimations of the RL of scratched connectors were performed, which were in good agreement with measurement results.

Stimulated Raman scattering (SRS) degrades the performance of wavelength-division-multiplexed (WDM) optical fiber communication systems by amplifying the longer-wavelength channels at the expense of shorter-wavelength channels, and making the spectral profile of transmission tilted. The spectral transmission tilt due to SRS of single-mode fiber span is measured by using a technique to separate it from the total loss profile of the fiber. An empirical model is developed to predict the transmission tilt for single-mode fiber of any fiber length under various optical power levels. The application of the model in test and evaluation of gain-flattened optical fiber amplifiers is introduced.

A quantitative description of the effects of fiber endface defects such as scratches and digs does not exist in the literature. We show, by considering surface scattering from the fiber endface, that such a description can be given in terms of a single parameter, which is a measure of the increase in backscattering due to the defect. We present our results in terms of some assumed values of this parameter.

Modern dynamic systems, such as manufacturing processes, are complex systems that demand continuous process monitoring, status evaluation and implementation of a variety of control strategies. An intelligent scheme is presented for control of manufacturing system under normal as well as fault conditions. A controller, well differentiated from plant, performs sequencing and scheduling of jobs under normal operating conditions while it performs reconfiguration operation under fault, breakdown or changed objective criteria. Reconfiguration is performed in terms of jobs re-routing and resource re-allocation, carried out by selecting a relocatable resource which would satisfy the new objective criteria. The re-routing problem is generally a multi-dimensional problem. A generalized framework is developed to deal quantitatively with the imprecision and complexity of the re-routing problem by using fuzzy multi-criteria analysis technique in conjunction with fuzzy Petri net representation of the system

In this paper, anti-jamming capabilities are proposed for a generic OFDM-based wireless communication system. The performance of a wireless system may severely degrade in presence of jamming or intentional interferences. A malicious entity can send strong interference or noisy signals in the same transmit frequency band thus preventing the intended receiver to correctly decode the transmitted data. As a countermeasure, our work proposes algorithms and techniques to restore the system performance in presence of such malicious entities. Proposed anti-jamming system consists of an adaptive framework that adapts itself to varying jammer behavior and wireless environment, and then, it chooses an optimal strategy to effectively cancel out the effect of jamming and channel fading. Optimization problem is formulated as a multi-objective criterion for maximization of system throughput and minimization of energy consumption. Simulation results computed in Rayleigh fading channels with different wideband jamming modes and powers show that the proposed system effectively cancels out the jamming and channel fading effects thus maximizing the system performance and minimizing cost of energy consumption. Copyright © 2013 John Wiley & Sons, Ltd.

Efficient data collection is challenging task in distributed power generation network. Use of sophisticated remote metering data collection techniques using advanced communication channels is receiving significant attention recently. On the other hand intelligent agents are widely being used to develop autonomous applications and have emerged as an attractive approach in developing power system solutions. To collect data from remote generating units and relevant weather stations located in heterogeneous environment, we have developed an novel agent based model for efficient data collection The proposed model switches to appropriate and economical communication channel based upon availability to collect timely data from remote stations. This model has been applied to Pakistan WAPDA's generation network and has produced accurate and timely results.

Accurate load forecasting is essential for energy planning and load management. This paper presents long term industrial load forecasting (LTLF) using Nonlinear Autoregressive Exogenous model (NARX) based Feed-Forward Neural Network (FFNN) method, Support Vector Regression (SVR) and Neural Network models. It is applied to data sets obtained from National Transmission and Dispatch Company (NTDC) of Pakistan, ranging from 1970 to 2010. Several influencing load factors are examined. Comparison of results obtained by all three techniques is presented which portray a high acceptable accuracy with 2.09% Mean absolute percentage error (MAPE) on monthly and yearly demand estimation for industrial sector.

In this paper, a cognitive system for link adaptation of Wi-Max physical layer is presented. The proposed cognitive system makes the Wi-Max physical layer adaptive to the wireless channel. It monitors the wireless channel as well as the system performance and then by choosing optimal transmission parameters adapts the physical layer thus maximizing the latter. The cognitive system is based on Support Vector Machine (SVM) technique with a novel feature set used for the adaptation purpose in Wi-Max. The wireless channels used in our simulations are Stanford University Interim (SUI) channel models combined with a range of SNR values‥ Simulation results show that the proposed cognitive system improves the Wi-Max system performance.

The website census is an effort to enumerate all the websites on the World Wide Web (WWW) without using crawling. Crawling is a traditional way of website discovery. It is conceptually simple but the very size of the WWW makes the implementation complex and resource demanding. The enormous amount of bandwidth, a huge persistent storage pool, a sufficiently large cluster of machines for data processing and a complex set of software systems are just a few examples of the needed resources. In this work, we use exhaustive IP range probing to detect the presence of a web server on TCP port 80. Although this probing is exhaustive in nature, it is lightweight in terms of resource demands. This enumeration of websites has many applications. The most obvious is to use it as a seed to the conventional crawling. It can be refined to be used as a top level domain (TLD) specific seed for targeted crawling.

In this paper, we establish a relationship between resource discovery protocol and cluster head election procedure. While doing so, we propose a multi-resource-criteria cluster head election mechanism that reduces the computational and communication overhead incurred in resource discovery. The consequent resource discovery protocol thus necessitates a minimalist exchange of information that we provide through custom packet formats and message flows. The extent of improvement thus achieved in the proposed protocol over existing resource discovery mechanisms is shown by performance evaluation.

Wireless Sensor Networks are included in today's important and evolving communication technologies. The size of sensors operating wirelessly decreases with the advent of advancement in device processing technologies like micro- and nano-electromechanical systems. This decrease in dimensions of sensors causes serious problem for battery storage capacity.We address this issue and propose a model of communication and recharging of Wireless Sensor Network (WSN) nodes simultaneously using passive optical communication. We propose both Line-of-Sight and Quasi-diffuse communication for this purpose. There are some situations where direct LOS is better option while at non-line-of-sight, the energy of a multi-spot Quasi-diffuse beam can be utilized. In our model we have used modified Corner Cube Retroreflector (CCR) and a newly proposed device Thinfilm Corner Cube Retroreflector (TCCR) for passive communication and recharging sensor nodes. These devices have large angle of diversity due to which they can provide communication facility to large areas. Our analysis shows that the proposed model could show better performance and significant increase in network life time.

In this paper, we analyze virtual machine (VM) scalability on multi-core systems for compute-, memory-, and network I/O-intensive workloads. The VM scalability evaluation under these three workloads will help cloud users to understand the performance impact of underlying system and network architectures. We demonstrate that VMs on the state-of-the-art multi-core processor based systems scale as well as multiple threads on native SMP kernel for CPU and memory intensive workloads. Intra-VM communication of network I/O intensive TCP message workload has a lower overhead compared to multiple threads when VMs are pinned to specific cores. However, VM scalability is severely limited for such workloads for across-VM communication on a single host due to virtual bridges. For across local and wide area network communication, the network bandwidth is the limiting factor. Unlike previous studies that use workload mixes, we apply a single workload type at a time to clearly attribute VM scalability bottlenecks to system and network architectures or virtualization itself.

One of the most critical limiting factor for a Wireless Sensor Network (WSN) is its battery life. Therefore, a very desirable feature of WSN would be its rechargability to remain operational over longer period of times. However, the nodes needing recharge may not be accessible. In this paper, we present a battery recharge model in WSNs for inaccessible or hard to access environments, at distances up to several hundred meters, using variable power Infrared (IR) laser. While bulk of the sensor network comprises of sensing nodes, the juncture nodes are the ones that relay data towards sink -resulting into faster battery depletion. We present a recharge mechanism for juncture nodes, that utilizes Free Space Optics (FSO) over RF-cliques using IR-laser, Corner Cube Retroreflectors (CCRs) and beam-steering lasers. A Thinfilm Corner Cube Retroreflector (TCCR) is also proposed as a variant to the standard CCR to realize selective recharging. The proposed mechanism provides recharge-ability both for on-demand recharging and scheduled recharging.

Software maintainability has always been a significant factor in the success or failure of any software product. There are numerous ways to calculate software maintainability but none of them has been able to grab as much industrial acceptance as the maintainability index (MI). MI can be calculated with the help of various tools, however selection of an appropriate tool for specific application is a critical research issue. This indicates that there is a dire need to clearly identify behavior of MI tools used for calculating software maintainability for various software source code scenarios. For this purpose we have analyzed behaviors of various MI tools with different MI parameters using a variety of test scenarios. We have developed a set of benchmark MI parameters test-cases for available MI tools to compare their results on the basis of features they support. We then executed the test scenarios on selected proprietary and open-source MI tools and evaluated their strengths and weaknesses on the basis of test results. The results highlighted weaknesses of some of the MI tools and helped us in making recommendations for selection of appropriate tool for specific application having better ability to determine the maintainability of the software system in terms of ldquomaintainability indexrdquo.

Wireless and mobile technology has transformed the didactic world. M-Learning is an emerging field which blends wireless technology and mobile computing to educate the world. This study investigates the effectiveness and viability of cellular technology to teach and train distance learners. The research answers following questions with reference to distance learning in Pakistan but not limited to it: Is this feasible to use cellular technology to educate people on mass scale? How can cellular technology help the Government of Pakistan face the challenge of providing education for all? What can be the motivations for the use of cellular technology instead of TV, radio and internet? What can be the limitations that may hinder the use of mobile devices for learning purpose? The distance learning models of Allama Iqbal Open University of Pakistan (AIOU) and Virtual University of Pakistan (VU) are studied to address the readiness of M-Learning environment in such universities.It is found that cellular technology can increase the efficacy of distance education. It is well suited to teach the language skills and information technology courses. We can use cellular technology as a supplement to the existing learning technologies to reaching huge student masses, in a timely and cost effective manner, through a variety of devices and over a diverse terrain.

This paper presents the comparative results of legacy TCP protocol with TCP detection and recovery (TCP-DR) over infrastructure based wireless networks. The newly proposed architecture of TCP-DR minimizes the losses due to channel errors and short disconnections. It enhances the TCP Reno functionality by modifying modules at the base station, which mitigates the bandwidth under utilization problem over infrastructure-based wireless network communication. The simulation results illustrate that performance can be improved up to 43% in the presence of high channel errors and short disconnections.

Due to separation and effective management of control and data planes, the optical burst switching (OBS) has been considered as a best switching technique for next generation all-optical networks. In order to implement OBS control plane three types of control and reservation architectures have been presented in literature e.g. centralized, distributed and hybrid. The hybrid architecture, presented by the authors, inherits the best features of distributed and centralized architectures such as scalability features of distributed model and best resource utilization of centralized model, In this paper a dynamic resource management for the hybrid architecture in the OBS network is presented. A design of different database tables required by different software modules to manage network resources during connection establishment/teardown phases is presented. A resource management algorithm is also designed for managing resources on the fly taking care of steps involved for lightpath establishment.

System security and privacy always have to face new confronts. Continuous updates in the operating systems and anti-virus applications strive to amplify the system security level. In recent years 'key-loggers' have proved to be one of the prevalent intimidations to security and privacy. Key-logger is a surreptitious surveillance application, which is used to keep record of user's activities on the computer in various ways like keyboard logging, screen logging, mouse logging and voice logging, completely in imperceptible mode. Although key-loggers can also be used for prolific purposes but due to the tremendous increase in the Internet usage, the caustic use of key-loggers simply surmounts its advantages. Key-loggers have gained so much supremacy in their execution that they have become a serious intimidation to the privacy and security of a computer. The fact which makes the key-loggers more perilous is their undetectable nature against anti-virus and spy-where applications. This paper discusses some existing techniques of fortification against key-loggers and also exemplifies a new technique along with its proved advantages.

Summary This research work introduces some novel techniques for interference-resilient OFDM wireless communication. Firstly, novel schemes for spatial multiplexing and interference cancelation based on signal subspace estimation are proposed. Secondly, the OFDM system is designed such that it meets three main objectives simultaneously, namely, (i) interference-resiliency, (ii) throughput maximization, and (iii) energy consumption minimization. Interference-cancelation techniques in prior art mostly consider maximization of throughput without any focus on energy consumption. On the other hand, the literature in energy minimization is limited to interference-free environments. Most of the previous techniques also have a drawback that they cannot operate in smart or dynamically changing interference environments. The focus here is on interference-resilient communication with equal attention to both throughput and energy-efficiency maximization in dynamic hostile environments. The optimization problem is formulated, and then optimal policies and switching thresholds are found for throughput and energy-efficient interference-resilient communication. Methodologies for estimating the channel and jammer conditions and then adapting the transmission strategies accordingly are proposed. Moreover, to have an effective defense against smart jamming scenario, a constant-payoff scheme is also introduced. Simulation results are compared with previous techniques that demonstrate the efficacy of proposed research. Copyright © 2015 John Wiley & Sons, Ltd.

Generalized multi-protocol label switching (GMPLS) which is also referred as multiprotocol lambda switching, supports devices that not only perform packet switching but also the devices that perform switching in domains of time, wavelength and space. This document provides the comparative analysis of the routing protocols involved in GMPLS networks. Open shortest path first (OSPF) and intermediate system to intermediate system (IS-IS) are the routing protocols being used in GMPLS for intra domain communications. We compare these protocols in terms of their basic features, traffic engineering (TE) extensions and enhancements provided in these protocols for support of GMPLS.

Mobile ad hoc networks have become, quite common nowadays. The usage of voice and video applications over these networks has created various challenges for research community. Real-time applications require certain guarantees in terms of throughput, delay, jitter and packet loss ratio from the underlying network. Legacy MAC layers do not provide service/traffic differentiation and treat both real-time and best-effort traffic equally. We propose an architecture for heterogeneous ad hoc networks that provides service differentiation. It gives better treatment to high priority traffic. More transmission time is allocated to high priority traffic, which improves its throughput and reduces end-to-end delay. Real-time traffic is allowed to transmit a burst of packets without contending for channel access, known as transmit opportunity (TXOP). A novel route, repair scheme, called AODV real repair (AODV-RR) is also proposed that tries its best to locally repair a broken route and minimize the real-time packet loss under heavy traffic load

In recent years, wireless LANs have been widely deployed in public places because of its low cost and high-speed connectivity. To cover larger areas, many APs are required which necessitate the use of handoff between different APs. Therefore handoff latency has become essential issue in wireless LANs. The delay caused by handoff process affects the quality of real-time applications like VoIP. So, in order to resolve this problem, an improved fast handoff mechanism is required that can minimize the overall handoff latency enough to run voice and video applications seamlessly. Handoff consists of three phases including scanning, reauthentication, and reassociation. Scanning is the most time consuming phase among all three. We propose a fast handoff scheme in which channels are scanned prior to the time of handoff. This novel approach almost eliminates scanning delay by using a pre-scanning algorithm and it takes only few milli seconds by using a dynamic caching mechanism

Mobile ad-hoc networks (MANETs) are temporary wireless networks useful in emergency rescue services, battlefields operations, mobile conferencing and a variety of other useful applications. Due to dynamic nature and lack of centralized monitoring points, these networks are highly vulnerable to attacks. Intrusion detection systems (IDS) provide audit and monitoring capabilities that offer the local security to a node and help to perceive the specific trust level of other nodes. We take benefit of the clustering concept in MANETs for the effective communication between nodes, where each cluster involves a number of member nodes and is managed by a cluster-head. It can be taken as an advantage in these battery and memory constrained networks for the purpose of intrusion detection, by separating tasks for the head and member nodes, at the same time providing opportunity for launching collaborative detection approach. The clustering schemes are generally used for the routing purposes to enhance the route efficiency. However, the effect of change of a cluster tends to change the route; thus degrades the performance. This paper presents a low-overhead clustering algorithm for the benefit of detecting intrusion rather than efficient routing. It also discusses the intrusion detection techniques with the help of this simplified clustering scheme.

TCP developed for wired networks assumes congestion as the reason of packet loss. This assumption might not be true for infrastructure based wireless networks like cdma2000 packet data networks due to other reasons of packet loss like higher bit error rate, hard handoffs, limited bandwidth and multi-path fading. Hence knowing the reason of packet loss is important. We propose a TCP congestion window optimization mechanism for cdma2000 packet Data Networks that introduces new flags in TCP packet at PDSN to make both communicating entities aware of the reason of packet loss. Loss-aware communicating ends initiate TCP slow start mechanism only if the reason of packet loss is congestion not data corruption