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The Discrete Wavelet Transform (DWT) is a unique signal analysis approach that has been actively applied to a range of difficulties in image processing in recent years. Windowing with varying area sizes is what makes it so powerful. DWT allows us to use small areas where we want high-frequency information more effectively. Wavelet research has picked up steam in the last few years. When it comes to digital signal processing and communication, DWT can be used in a variety of ways. As a voice and picture coding technology, it has many of the characteristics of primitive models of the human visual system. When this is taken into account, it is possible that coding methods will produce compression that is more pleasing to the eye than those that aim to minimise square error. Patterns and breakdown points can be revealed in data using DWT, which other approaches miss. DWT is becoming increasingly popular and is the subject of extensive research, in part because of its many advantages.

Metal/metal oxide nanocomposites (NCs) have been attracting significant attention in recent times because of their applications in the fields of energy and environment. In the present work, we investigate the photocatalytic and electrochemical performances of Ni/NiO NCs synthesized by a facile and cost-effective reduction method using lithium salt as the dopant. Lithium influences the size, morphology and structural constitution of the final product. A variation in the lithium percentage was seen to have a direct effect on the Ni content. The structural conformation of the samples has been analyzed by XRD and further confirmed by XPS. A low optical energy bandgap (∼3.7 eV) and a mesoporous structure of the as-prepared samples were seen to play a crucial role in achieving the photocatalytic degradation of the cationic organic dyes concomitant to its electrochemical activity. On illumination with UV light, the Li-doped Ni/NiO NCs demonstrated rapid degradation of crystal violet and methyl violet 2B dyes. The synergism arising due to the substitutional doping of lithium and the presence of metallic nickel leads to efficient photodegradation of the dye pollutants by the catalysts. Further, the Li-doped Ni/NiO NCs displayed a better electrochemical performance than the undoped samples. The NC with 1 wt% Li exhibited the best values of specific capacitance (276.2 F g−1 at 5 A g−1) with an excellent cycling ability (

In connection with our continuous efforts in the synthesis of derivatives from major compounds isolated from traditional medicinal plants, in the present study we have attempted to synthesize the furan-conjugated aloe-emodin derivatives (

In connection with our continuous efforts in the synthesis of derivatives from major compounds isolated from traditional medicinal plants, in the present study we have attempted to synthesize the furan-conjugated aloe-emodin derivatives (5a–j) using a three-component reaction. The synthesized derivatives were assessed for anticancer activity against five different cancer cell lines using the in vitro MTT assay and the results showed that most of the derivatives are potent against cancer cells comparing with the control. Compounds 5a and 5e showed excellent activity against all the cancer cells with less than 12.5 µM and arrested the cell cycle at the G0/G1 phase in both CAL27 and SCC9 cells. Compound 5e induces the early apoptosis in CAL27 cells and compounds 5a and 5e induce early and late apoptosis, respectively, in SCC9 cells. Moreover, compounds 5b, 5c, 5i, and 5j showed excellent anti-inflammatory activity in LPS-stimulated RAW 264.7 cells by inhibiting IL-6 production. The molecular docking studies revealed that compound 5e has strong interaction with the CLK kinase and protein kinase II through hydrogen binding Asp325 and Lys290.

The Smart Grid is an advanced digital two-way power flow power system capable of self-healing, adaptive, resilient and sustainable with foresight for prediction under different uncertainties. In this paper, a survey on various Smart Grid enabling technologies, Smart Grid metering and communication, cloud computing in Smart Grid and Smart Grid applications are explored in detail. Opportunities and future of Smart Grid is also described in this paper. For Smart grid enabling technologies Smart meters, smart sensors, vehicle to grid, plug in hybrid electric vehicle technology, sensor and actuator networks are explored. Advanced metering infrastructure, intelligent electronic devices, phasor measurement units, wide area measurement systems, local area network, home access network, neighborhood area network, wide area networks and cloud computing are explored for Smart Grid metering and communication. Home and building automation, smart substation, feeder automation is explored for smart grid applications. Associations of initial studies for the next step in smart grid applications will provide an economic benefit for the authorities in the long term, and will help to establish standards to be compatible with every application so that all smart grid applications can be coordinated under the control of the same authorities. Therefore, this study is expected to be an important guiding source for researchers and engineers studying the smart grid. It also helps transmission and distribution system operators to follow the right path as they are transforming their classical grids to smart grids.

Removal of the hazardous and endocrine-disrupting 2,4-dichlorophenol (2,4-DCP) from water bodies is crucial to maintain the sanctity of the ecosystem. As a low bandgap material (1.37 eV), NaBiS

Fig. 1 and the Graphical Abstract were created by Heno Hwang, scientific illustrator at King Abdullah University of Science and Technology (KAUST). The research reported in this publication was supported by funding from KAUST. The funding support from Department of Science and Technology’s Technology Mission Division (No. OST/TM O(EWO)/OWUIS20IS/TS-03 (G)) under the program “Optimal Water Use in Industrial Sector” is greatly acknowledged.

Concerns over environment and increased demand for energy have led the world to think about alternate energy sources such as the wind, hydro, solar and fuel cells. Out of these photovoltaic (PV) generation systems (PGS) become increasingly important all over the world due to its availability, cleanness, low maintenance cost, and inexhaustible nature. The probability of partial shading conditions (PSC) is also high for large PGS. Under PSC, the P–V curve of PGS exhibits multiple peaks, which reduces the effectiveness of conventional maximum power point tracking (MPPT) methods. In this paper, an improved particle swarm optimization (PSO) based MPPT algorithm for PGS operating under PSC is proposed. Conventional PSO is modified to meet practical consideration of PGS operating under PSC. Problem formulation, design details, and experimental results are discussed in detail. The proposed technique is independent of system, it is easy to implement, tracking efficiency is high and performance under PSC is good. The effectiveness of the proposed method is validated by analyzing the experimental results obtained from 110 W solar power generation systems.

The advent of COVID-19 has kept the whole world on their toes. Countries are maximizing their efforts to combat the virus and to minimize the infection. Since infectious microorganisms may be transmitted by variety of routes, respiratory and facial protection is required for those that are usually transmitted via droplets/aerosols. Therefore this pandemic has caused a sudden increase in the demand for personal protective equipment (PPE) such as gloves, masks, and many other important items since, the evidence of individual-to-individual transmission (through respiratory droplets/coughing) and secondary infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). But the disposal of these personal protective measures remains a huge question mark towards the environmental impact. Huge waste generation demands proper segregation according to waste types, collection, and recycling to minimize the risk of infection spread through aerosols and attempts to implement measures to monitor infections. Hence, this review focuses on the impact of environment due to improper disposal of these personal protective measures and to investigate the safe disposal methods for these protective measures by using the safe, secure and innovative biological methods such as the use of Artificial Intelligence (AI) and Ultraviolet (UV) lights for killing such deadly viruses.

Conventional maximum power point tracking (MPPT) algorithms fails to track peak power from a solar photovoltaic panel (SPV) effectively under rapidly changing atmospheric and partial shading conditions (PSC). To track peak power more effectively under these conditions, low cost, powerful soft computing (SC) have been introduced by the researchers. Due to the ability to solve non-linear problems, flexibility and adaptive nature, SC based MPPT techniques can track peak power under varying atmospheric conditions. Various SC based MPPT techniques have been proposed by researchers till date. Comprehensive studies on all these techniques are not available. This work summarizes working principle of various SC-MPPT techniques and are compared each other based on the certain parameters like accuracy, tracking efficiency, SPV array dependency, convergence time, complexity of algorithm, hardware implementation, ability to handle PSC’s and variables used. The information that is gathered and summarized in this paper will help researchers for future studies in this area.

Crank Shaft is one of the important components of an IC Engine. As the mechanical property of the crankshaft directly influence the trustability and longevity of the engine, the rigidity of the crankshaft acted upon by the alternative loads must be guaranteed in design. So it is required very much to untangle the model of crankshaft through the stress analysis using ANSYS software. In this paper, first the 3D model of the engine parts are built in the software ‘CATIA V5’ and are then transferred to ‘ANSYS’. The analysis of crank throw distortion and stress provides a conceptual support to enhance the design by weigh reduction.

In the present paper, a multivariate statistical modeling study of water quality data from different places of Kozhikode Gity, Kerala, India, has been conducted applying multiple linear regression (MLR), structural equation modeling (SEM), and adaptive neuro-fuzzy inference system (ANFIS) modeling. First, we combined water quality data from different places in the study area over different time periods to obtain a unified multiple linear regression (MLR) model. By mixing three data sets from different places and time periods in four different ways, different regression models were formed with total dissolved solids (TDS) as the dependent variable and calcium, magnesium, nitrate, sodium, chloride, potassium, total hardness, and sulfate as independent variables. The effectiveness of each model was then tested against a data set, which corresponded to a different period and location. One unmixed model and three mixed models showed similar performance. An SEM was developed for the data set, which is obtained by mixing all the three data sets. The same regression coefficients are found for the SEM and the corresponding MLR. An improvement in the sample size as a result of mixing of data sets could be thought of as the reason for this phenomenon. We thus selected the MLR obtained by mixing all three data sets as our unified model. For the mixed data set, we then developed an ANFIS model with calcium, magnesium, nitrate, sodium, chloride, potassium, total hardness, and sulfate as input variables and TDS as the output variable. On the external data set, the ANFIS model showed a better performance than the MLR model.

Tree-based learning techniques are considered to be one of the best and most used supervised learning methods. Tree-based methods empower predictive models with high accuracy, stability, and ease of interpretation. Unlike linear models, they map non-linear relationships pretty well. These methods are adaptable at solving any kind of problem at hand (classification or regression). Methods like decision trees, random forest, gradient boosting are being widely used in all kinds of machine learning and data science problems. Hence, for every data analyst, it is important to learn these algorithms and use them for modeling. This chapter guide the learner to learn tree-based modeling techniques from scratch.

This paper demonstrates the implementation of a QPSK/ time division multiple access (TDMA) narrowband (NB) satellite receiver using short preamble-based synchronization in the presence of timing, frequency and phase offsets, and with additive white Gaussian noise (AWGN). The narrowband satellite communication (NB-SATCOM) system, which is mostly preferred for low-rate data transfer, is primarily affected by large carrier frequency offset (CFO). The implemented receiver uses a 32-symbol short preamble for synchronization of time, large frequency and phase, and it gives better bit error rate (BER) performance at low energy per bit to noise density ratio (E b /N 0 ). As the proposed design uses short preamble, it is able to achieve a high level of spectral efficiency with less computational complexity. The functional verification of the synchronization algorithm is done using Matlab simulations and the algorithm implementation uses fixed-point C. The receiver design has been implemented for 24 TDMA channels in Texas Instruments (TI) multi-core C66x DSPs.

The silver nanoparticles (AgNPs) synthesized using hot water neen leaf extract (NLF) as reducing and stabilizing agent are reported and evaluated for antibacterial activity against chilli seed borne pathogens. The effect of extract concentration, contact time, pH and temperature on the reaction rate and the shape of the Ag nanoparticles were investigated. The data revealed that the rate of formation of the nanosilver size decreased significantly in the basic medium with different concentration (1 mM, 5 mM and 10 mM). Synthesized was characterized by UV-vis spectroscopy, X-ray diffraction, scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The nanoparticle synthesis using different concentration of silver nitrate and 5 mM was getting nano sized silver particles AgNPs. The silver nanoparticles were with an average size of 55 to 350 nm and mostly rod shape. The antifungal activity of synthesized AgNPs was observed in seed health test and different concentration of silver NPs (750 mg, 1000 mg and 1250 mg) were used for seed health test. The AgNPs at 750 mg concentration significantly inhibited the seed borne pothogens. Thus AgNPs showed broad spectrum antifungal activity at lower concentration and may be a good alternative therapeutic approach in future.

Investigations were undertaken to study the physiological effectiveness of different ornamental succulents under tropical condition. Six species of succulents were evaluated under four different growing environments. Results showed that the performance of succulents grown under conservatory house condition was found to be performed well and ideal with respect to chlorophyll, carotenoids, relative water content and photosynthetic rate than other growing environments. The succulent species viz ., Haworthia limifolia, Monadenium lugardiae and Aloe juvenna were the most suitable species for growing under conservatory house condition due to its high nocturnal CO 2 uptake and cell sap acidification which possess CAM metabolism. CAM involves nocturnal CO 2 uptake and fixation by cytosolic phosphoenolpyruvate carboxylase into malic acid that is stored in the vacuole causing nocturnal cell sap acidification. During the subsequent light period, malic acid is released from the vacuole in the form of malate that is then decarboxylated leading to deacidification of cell sap, formation of pyruvate or phosphoenolpyruvate and liberation of CO 2 . Repeated acidification and deacidification cycles represent a characteristic physiological feature of CAM metabolism in succulents which is best suited for xeric environment and possess high photosynthetic efficiency.

This study was aimed to develop the nanoform of a commercial fungicide Trifloxystrobin 25% + Tebuconazole 50% (75 WG) with broad spectrum of action for improving its antifungal activity against Macrophomina phaseolina. The fungicide commercially available as Trifloxystrobin 25% + Tebuconazole 50% (75 WG) was converted into its nanoform using ball milling method and assessed for its efficacy against the soil borne fungal pathogen M. phaseolina at various concentrations, namely 5, 10, 15, and 25 ppm using poisoned food technique. Nanoform of the fungicide was characterized using Scanning Electron Microscopy (SEM) and Particle Size Analyzer (PSA). The average particle size of nano Trifloxystrobin 25% + Tebuconazole 50% (75 WG) was about 108 nm. Fungicidal potential of nanoform was better in comparison to the conventional ones. Nanoform of the fungicide was effective at 10 ppm and it exerted hyphal abnormality, hyphal lysis and abnormality of sclerotial formation on M. phaseolina when tested under in vitro than control. This study suggests the possibility to enhance the antifungal activity of fungicide Trifloxystrobin 25% + Tebuconazole 50% (75 WG) towards the control of M. phaseolina. Key words: Antifungal, nanoformulations, chilli, Trifloxystrobin 25% + Tebuconazole 50% (75 WG), Macrophomina phaseolina.

A series of oxime ester-derivatives were prepared by utilizing the schizandrin (1), a major compound isolated from Schisandra grandiflora, which is deployed in different traditional system of medicine. The in vitro antiproliferative activities of the synthesized compounds were assessed against a selected panel of human cancer cell lines (A549, RKO P3, DU145 and Hela) and normal cell (HEK293). Several of these derivatives were found more potent in comparison to parent compound, schizandrin (1). Particularly, 4a and 4b demonstrated potent activity against DU-145 and RKOP3 cell lines with IC50 values of 3.42 µM and 3.35 µM respectively. To characterize the molecular mechanisms involved in antitumoral activity, these two compounds, 4a and 4b were selected for further studies. Cell cycle analysis revealed that both the compounds were able to induce apoptosis and cell cycle arrest at G0/G1 phase. To know the extent of apoptosis in DU145 and RKOP3 cell lines, Annexin V-FITC were performed. Moreover, the tubulin polymerization assay indicated that 4a and 4b exhibits potent inhibitory effect on the tubulin assembly. Molecular docking studies and competitive binding assay also indicated that 4a and 4b effectively bind at the colchicine binding site of the tubulin.

In the present study, inorganic bulk and nano nutrients of zinc oxide, titanium oxide, and silver nanoparticles were synthesized using the chemical reduction method and invigourated with chilli seeds cv. PKM 1 each at 750, 1000 and 1250 mg kg−1 by using template-free aqueous solution. After nanoparticles invigouration, the seeds were analyzed for various parameters such as germination (%), shoot length, root length, and seedling vigour. Other important parameters, such as electrical conductivity and antioxidant enzyme activity (catalase and lipid peroxidase), were also analyzed, which in turn reflected the enhancement of seed quality of chilli seeds when they were invigourated with ZnO, TiO2 and silver nanoparticles. The results indicated that the chilli seeds invigourated with ZnO nanoparticles at 1000 mg kg−1 enhanced the germination and seedling vigour in aged seeds.

In continuation of our investigation of pharmacologically-motivated natural products, we have isolated bergenin (1) as a major compound from Mallotus philippensis, which is deployed in different Indian traditional systems of medicine. Here, a series of bergenin-1,2,3-triazole hybrids were synthesized and evaluated for their potentials against a panel of cancer cell lines. Several of the hybrid derivatives were found more potent in comparison to parent compound bergenin (1). Among them, 4j demonstrated potent activity against A-549 and HeLa cell lines with IC50 values of 1.86 µM and 1.33 μM, respectively, and was equipotent to doxorubicin. Cell cycle analysis showed that 4j arrested HeLa cells at G2/M phase and lead to accumulation of Cyclin B1 protein. Cell based tubulin polymerization assays and docking studies demonstrated that 4j disrupts tubulin assembly by occupying colchicine binding pocket of tubulin.

The main aim of this paper is to provide the security for accessing the collaborative computing environment. Main thing here is using authentication method, users can access their collaborative environments. So normal authentication is not sufficient for collaborative environment, that is why here I am proposing two-factor authentication for collaborative environment.

This paper demonstrates a multi-core DSP-based implementation of variable data rate OQPSK/time division multiple access (TDMA) satellite receiver in the presence of timing, frequency and phase offsets, and with additive white Gaussian noise (AWGN). The implemented receiver uses a 64-bit short preamble for synchronization. It operates at a variable symbol rate of 220Ksps to 660Ksps and gives better bit error rate (BER) performance at low energy per bit to noise density ratio (E b /N 0 ). The proposed receiver operates at a carrier frequency offset upto 15% value normalized to symbol rate. Matlab simulations are used for functional verification of the synchronization algorithm and fixed-point C is used for algorithm implementation. The receiver design is prototyped for 12 TDMA channels in Texas Instruments (TI) multi-core C66x DSPs. The design and implementation of this receiver have been done for C-DOT indigenous satellite project.

In this paper, an attempt was made to study the physico-chemical properties of ground water of the Kozhikode district, Kerala, India, by applying multivariate statistical methods on samples collected from various parts of the study area. Combining principal component analysis and multiple linear regression (MLR), we developed a regression model for predicting total dissolved solids (TDS) in terms of calcium, magnesium, nitrate, sodium, chloride, potassium, bicarbonate and sulfate. This study revealed that statistically, calcium is the most significant component of TDS in the study area. The relevance of the regression model with respect to experimental data was further evaluated by applying structural equation modeling (SEM).

Ground water is the principal source for drinking water and other activities in Kozhikode town. Monitoring the ground water quality therefore is of utmost importance. In this paper a multivariate statistical analysis of quality of ground water has been carried out, based on thirty data points of water shed in Kozhikode city, Kerala, India. The parameters examined were PH, Electric conductivity, Total Dissolved Solids, Total Hardness, Chlorides, Calcium and Magnesium, Sodium, Potassium, Bicarbonates and Sulphates. A methodology for characterizing ground water quality of watersheds based on the above data that mingle multiple linear regression, principal component analysis and structural equation modeling is presented. The aim of this work is to analyze hydro chemical data in order to explore the groundwater samples and the origin of water mineralization, using mathematical method and modeling. Thus, with the help of MATLAB, a regression equation is explored for the sampled ground water. The structural equation modeling which has been carried out using IBM-SPSS Amos, allows a simultaneous analysis of the entire system of parameters.

The low oral bioavailability of atenolol is primarily because of its poor absorption from the lower gastrointestinal tract. Gastroretentive dosage forms provide an opportunity to deliver the drug with absorption window in the proximal part of the GIT thereby increasing their bioavailability. The objective of this study was to develop a dosage form for atenolol with the objective of increasing the gastric residence and there by its oral bioavailability. Different formulations of floating tablets of atenolol (AT1-AT10) were prepared by varying the composition of hydroxypropyl methyl cellulose (HPMC) K100, lactose and citric acid. The tablets were evaluated for various parameters like friability, weight variation, content variation, floating lag time, total buoyancy and in vitro dissolution. The physicochemical properties of the prepared formulations were found to possess adequate physical integrity. Formulation AT8 showed the lowest floating lag time with 14 h buoyancy. Drug release was found to be dependent on the concentration of HPMC K100 and lactose in the formulation. Further, the increase in amount of citric acid leads to increase in atenolol release rate while reduces the floating time. The findings revealed that the formulation AT8 retarded the atenolol release (~73% in 12 h) and followed zero order kinetics. The in vitro data observed here substantiate the potential of the prepared formulation to provide adequate drug release and buoyancy to improve the bioavailability of atenolol, which necessitate further in vivo studies.

This paper demonstrates the implementation of bit synchronization and delayed decision feedback equalization for Enhanced Data rates for GSM Evolution (EDGE) system on TMS320C6424 DSP. EDGE makes use of training sequence for channel estimation and inter symbol interference (ISI) cancellation by use of delayed decision feedback equalization. Modulated baseband in-phase (I) and quadrature (Q) signals are generated using Agilent E4438C Vector signal generator and faded using Agilent fading simulator, is used as input to the DSP. Bit Error Rate (BER) performance of uncoded bits for Packet Data Traffic Channel (PDTCH) meets the EDGE standards. Software implementation uses fixed-point C and Integrated Development Environment (IDE) used for development is code composer studio (CCS). Prototyped our design in Texas Instrument TMS320C6424 DSP and verified for all propagation models as per the EDGE standards. The design and hardware implementation of this Demodulator is done for C-DOT indigenous Shared GSM Radio Access Network (SGRAN) Base Transceiver Station (BTS) project.

Real time system is a system in which the computation not only depends on producing a correct output, but the output should be delivered within predetermine timing constraint called deadline. As humans, we handle scheduling issues every day. For example, a student must accomplish homework by the appropriate due date, a professor must complete the rough draft of a paper by the submission date, etc., where we have only one task to accomplish, meeting that deadline probably would be very simple. Our lives, however, contain many tasks that have deadlines tax forms, car inspections, meetings, classes, etc. Thus, we must use some sort of scheduling technique to “juggle” our various tasks, so that they all are completed by their appropriate deadlines. As a result, many scholars develop different static and dynamic scheduling algorithms, which are best suited for both uniprocessor and multiprocessors. This paper work will focus on proposing a new dynamic scheduling algorithm. Because, it is found that the well-known uniprocessor dynamic scheduling (EDF (earlier deadline first) and LLF (least slack time first)) algorithms have many context switching and many probability of overhead occurrence (deadline-tie and laxity-tie respectively) which will degrade the performance of the whole system. The paper proposes a dynamic scheduling algorithm that has low context switching and totally reduce the probability of overhead occurrence by combining the deadline and slack to give priority for each task in the ready queue.

Our world is increasingly driven by sophisticated networks of advanced computing technology, and the basic operation of everyday society is becoming increasingly vulnerable to those networks shortcomings. The implementation and upkeep of a strong network defense is a substantial challenge, beset not only by economic disincentives, but also by an inherent logistical bias that grants advantage to attackers.Network Security Attacks and Countermeasures discusses the security and optimization of computer networks for use in a variety of disciplines and fields. Touching on such matters as mobile and VPN security, IP spoofing, and intrusion detection, this edited collection emboldens the efforts of researchers, academics, and network administrators working in both the public and private sectors.This edited compilation includes chapters covering topics such as attacks and countermeasures, mobile wireless networking, intrusion detection systems, next-generation firewalls, and more.

As Internet and its technologies are improving with rapid pace, there are security threats growing with same pace. The malicious software such as worm is causing such threats to IT systems linked to information super highway. The worms are capable of replicating themselves and infect systems over network. Their traffic propagation can be detected by employing anti worm or virus software. However, there is a new type of worm that can camouflage itself so as to prevent anti worm software from identifying it. The difference between normal worm's traffic and C-worm's traffic can't be found when time domain is considered. However, in terms of frequency definitely it can be differentiated. Based on this hypothesis, this paper presents novel schemes such as PSD and SFM that are capable of differentiating the traffic of C-worm from background traffic. The empirical results revealed that our schemes are effecting in detecting camouflaging worms effectively besides identifying normal worms. Keywords - Traffic propagation, worm, camouflaging worm, time domain, and frequency domain. I. Introduction Worm is a word with broad meaning. It refers to any program which is malicious in nature. Such program could be a VIRUS, worm etc. They have common features which are also there with biological virus. The common features include that they replicate themselves and also propagate from one machine to another machine. The means of propagation is only through infected storage media and also networks of all kinds including those without wire. Active worms continuously strive to propagate themselves to other systems and make them insecure. This is a problem which has been around ever since the world came across malicious programs for the first time. Some worms include Slammer (2), Sasser (3) and Code-Red (1). Some worms will work together by forming bonnets and cause more damage to IT systems. The attacks made by such worms include DDoS; attack to obtain sensitive information; destroying data (5) and also put forth unwanted materials such as advertisements. Many such worms are commonly known as malware (malicious software). This includes virus as well. The virus could be boot sector virus, file virus, love virus, time bomb virus, Trojan virus and so on. There is enough evidence in the history that some people have made it their business to create malware and also solutions to prevent them. This is major problem in the world of computers. This man made evil will continue posing threats to IT systems and also cause the businesses to loose confidential information and thus loosing confidence and profits in the business (4), (6). Researchers also predicting the possibility of malicious programs such as bonnets to collaborate and cause more security threats to IT world. Such collaborated bonnets is known as super bots (7). As there were reports of worms causing major damage to IT systems, the past few years saw significant research in the area of worms. Worm detection and prevention is an essential task required by all systems involved in IT. Thus the presence of anti-worm software is felt and the same is done through research. The process of identifying the worms by observing their scan traffic much anti-worm software succeed in detecting and also preventing any damage to IT systems. The emergence of Internet and also other networking facilities and communication systems paved way for the increase of threats caused by worms. Studying different kinds of worms and their impact on the IT systems and also prevention techniques are to be given paramount importance. When a worm infects a system, it will propagate its traffic in the system to cause damage to its data. It also strives to propagate the traffic to other systems though infected storage media and networks to other systems in the real world. They keep on identifying IP addresses of systems in the world and infect them though the ways known to them. The common way they follow is generating scan traffic in the time domain and frequency domain. Thus they make all the systems attacked by worms vulnerable to security threats. There is a possibility of loosing companies' sensitive information that leads to collapse of business or losing in revenues in large scale. The patterns of the worms (2), (8), (9) are increasing day by day. The more patterns of worm propagation is known, the more possibility to detect and prevent them. The assumption of all software in the world that is sued to combat worms is that the worms generate scan traffic and try to replicate themselves and infect systems in the same network and remote networks. The patterns are generally having same characteristics so as to enable anti-worm to detect them. However, a new class of worm has come into existence. This new worm is capable of hiding its presence.

In the field of robotics, the two wheel mobile manipulator has the potential to perform wide range of applications. Balancing of the system becomes a bothering task due to the highly unstable nature of the system. Dynamics of wheeled mobile manipulator are derived by the basics of energy balance equation by approximating double inverted pendulum dynamics. Control method for balancing the two wheeled mobile manipulator using H-infinity controller (H∞) is discussed in the work. H-infinity control methods are developed to design systems which have the desired dynamic behavior and are robust with respect to perturbations. Settling time required to achieve stability of the system and maximum deviation from desired value using linear quadratic regulator (LQR) controller and H-infinity controller are compared. Designing and simulations are carried out to check the validity of the proposed method and the results prove the effectiveness of the proposed method.

The benefits of six-sigma quality standard implementation are realized by the manufacturing sector very well and most of the cases reaped astounding benefits. This paper presents an extensive review on the services, six-sigma, and study the Critical Success Factors, Critical to Quality Characteristics and Key Performance Indicators in medium scale hospitals in Tamilnadu, India. Can health care approach the near perfection of Six Sigma in actual practice? . General Electric has begun to apply the same Six Sigma methods that worked to improve its manufacturing processes to its other, more service-oriented businesses. We believe, however, that asking this question must not be an excuse for failing to embark on the journey. Health care now frequently produces defects at rates as high as 500,000 per million––as exemplified in failures to recognize and treat clinical depression (Wells et al. 1989) or control hypertension (Udvarhelyi et al. 1991). Enough examples of improvement exist to conclude that we can do much better. In order to improve health service quality focus on health service process is necessary. Six-sigma is a philosophy which also concentrates on the improvement of process. So, six-sigma if properly applied can be useful for health services. The wider applicability of six-sigma depends on identification of key performance indicators (KPIs) for different types of health service processes. A case study is conducted in a medium scale hospital to identify, analyze and rank the critical success factors for Six sigma implementation available in literature, critical to quality characteristics (CTQs) ,KPIs and hurdles in the hospitals which affect possible quality improvements. This study will be helpful to both practitioners and researchers.

Nowadays, Computer Networks tend to be large and diverse systems that communicate using wide selection of protocols. This complexity made the desire for more sophisticated tools to watch and troubleshoot network traffic. Network traffic monitoring is can be quite a network diagnostic tool that monitors local area networks and provides a graphical display of network statistics. While collecting information through the network's data stream, network monitor displays the source address of the computer that sent a frame onto the network, the destination address of the computer that received the frame and also the protocols employed to send the frame. The procedure through which network monitor collects this information is known as Capturing. Automatically, the network monitor gathers statistics on all of the frames it detects on the network into a capture buffer that is a reserved storage area in memory. To capture statistics on merely a specific subset of frames, we could discriminate these frames by designing a capture filter. To work with network monitor, the computer will need to have a network card that supports promiscuous mode. This paper targets on the usage of packet capturing library Jpcap for monitoring, analyzing and reporting Distributed Denial of Service (DDoS) Attacks.

Distributed Denial of Service (DDoS) attacks in the internet disrupts the availability of a service or resource. Massive Distributed DoS attacks have the potential to severely decrease backbone availability and can virtually detach a network from the Internet. Because of the seriousness of the problem many defense mechanisms have been proposed to combat these attacks. This paper presents a Multi-layered probabilistic model for DDoS attacks and evaluated the performance of the system. Furthermore, important features of each attack and defense system category are described and advantages and disadvantages of each proposed scheme are outlined. The goal of the paper is to place some order into the existing attack and defense mechanisms, so that a better understanding of DDoS attacks can be achieved and subsequently more efficient and effective algorithms, techniques and procedures to combat these attacks may be developed.

Web is a collection of inter-related files on one or more Web servers. Web mining is one of the mining technologies, which applies data mining techniques in large amount of web data to improve the web services. Wide Web provides every internet citizen with access to an abundance of information, but it becomes increasingly difficult to identify the relevant pieces of information. Research in web mining tries to address this problem by applying techniques from data mining and machine learning to Web data and documents. The Web Mining is an application of Data Mining. Without the internet, life would have been almost impossible. The data available on the web is so voluminous and heterogeneous that it becomes an essential factor to mine this available data to make it presentable, useful, and pertinent to a particular problem. Web mining deals with extracting these interesting patterns and developing useful abstracts from diversified sources. The present paper deals with a preliminary discussion of WEB mining, few key computer science contributions in the field of web mining and outlines some promising areas of future research.

Drought affects hundreds of millions of people in the developing world and causes serious disruption of social and economic activities. Preparedness is better than relief and information is the backbone of drought preparedness. In this paper we report the results from a study in the use of GIS-derived products to assess micro-level drought vulnerability, taking a cluster of 17 villages in the South Central India as the study area. An internet-connected rural information center, linked to village knowledge centers, played a key role in testing the utility of this product, and the associated local-level predictions for seasonal rainfall.

Tuberculosis is a chronic systemic granulomatous disease which rarely affects the oral cavity. Oral lesions can be either primary or secondary to systemic tuberculosis, the former being rare. This is a never-before reported case of primary tuberculosis presenting as a localized diffuse gingival enlargement in an 11-year-old Indian female patient. The diagnosis was reached through identification of positive histopathological features, Tuberculin test results, presence of anti-tubercular antibodies confirmed by a polymerase chain reaction. In view of the recent increase in the incidence of tuberculosis and the prevalence of the same, it is reasonable to include tuberculosis in the differential diagnosis of gingival enlargements. This is essential to avoid any serious complications for both the clinician and patient due to a delay in the diagnosis of such a rare but plausible oral condition.

With the advent of effective drug therapy, tuberculous lesions of the oral cavity have become so rare that they are frequently forgotten. Primary gingival tuberculosis is extremely rare and usually manifests as ulcer. We report the first case of primary tuberculosis manifesting as gingival enlargement, which was the only presenting sign of tuberculosis. Diagnosis was based on histopathology (hematoxin and eosin staining), complete blood count, polymerase chain reaction assay and immunologic investigation with the detection of antibodies against Mycobacterium tuberculosis. The possibility of gingival enlargement due to drugs, leukemia, fungus and sarcoidosis was ruled out. Antituberculous therapy over 6 months was followed by surgical excision of the residual enlargement under local anesthesia. After 1-year follow-up there was no recurrence of the disease. This case emphasizes the need for dentists to include tuberculosis in the differential diagnosis of gingival enlargement so that they may play a role in its early detection.

Big Data is a relatively recent phenomenon, but has already shown its potential to drastically alter the relationships between businesses, individuals, and governments. The issues surrounding privacy of the online users (Mayer-Shoenberger, Cukier 2013) and the overall ethical challenges involved (Schroeder, 2014) make big data a topical issue, especially in the aftermath of the Snowden revelations. Many organisations now control vast amounts of raw data, and those industry players with the resources to mine that data to create new information have a significant advantage in the big data market. The use of predictive analytics in processing information tracked across different platforms to identify trends in the behaviour of individuals further adds value to big data (Fotopoulou, 2014) and makes it an important asset for any commercial entity. This rapid commodification of personal data has given rise to a new approach with regard its legal protection in the era of big data: a shift from the traditional privacy protection regime to a wider protection under property law is considered by scholars as an appropriate legal response to the phenomenon of monetisation of personal data, once seen through the lens of big data (Victor, 2013).\ud \ud The aim of this chapter is to identify the legal grounds for the ownership of big data: who legally owns the petabytes and exabytes of information created daily? Does this belong to the users, the data analysts or to the data brokers and various infomediaries? The chapter presents a succinct overview of the legal ownership of big data by examining the key players in control of the information at each stage of the processing of big data. It then moves on to describe the current legislative framework with regard to data protection and concludes in additional techno-legal solutions offered to complement the law of big data in this respect, with a particular focus on the European context .