Search

The outbreak of Coronavirus Disease as a pandemic has resulted in a huge saddle on health infrastructure. Preventive measures such as quarantine, social distancing, isolation, and community containment play a pivotal role to contain the spread of exponentially growing COVID cases. This huge burden permitted authorities for institutional/home quarantine for the suspected persons. The biggest challenge for institutional/home quarantine is to monitor and track the movement of quarantined persons. These suspected cases pose a serious threat in outbreak and transmission of the disease. In this paper, an intelligent-Quarantine Monitoring System (iQMS) has been presented which comprises of a wearable IoT-based wristband, bundled with an android mobile app to track and report the absconding quarantined subjects in near real-time. The iQMS incorporates a cloud-based solution with IoT sensors using a global positioning system (GPS) based tracker for geo-fencing breach. The proposed system will facilitate the authorities in remote monitoring and tracking of identified subjects.

The Coronavirus Disease (COVID-19) caused by SARS-CoV-2, continues to be a global threat. The major global concern among scientists and researchers is to develop innovative digital solutions for prediction and control of infection and to discover drugs for its cure. In this paper we developed a strategic technical solution for surveillance and control of COVID-19 in Delhi-National Capital Region (NCR). This work aims to elucidate the Delhi COVID-19 Data Management Framework, the backend mechanism of integrated Command and Control Center (iCCC) with plugged-in modules for various administrative, medical and field operations. Based on the time-series data extracted from iCCC repository, the forecasting of COVID-19 spread has been carried out for Delhi using the Auto-Regressive Integrated Moving Average (ARIMA) model as it can effectively predict the logistics requirements, active cases, positive patients, and death rate. The intelligence generated through this research has paved the way for the Government of National Capital Territory Delhi to strategize COVID-19 related policies formulation and implementation on real time basis. The outcome of this innovative work has led to the drastic reduction in COVID-19 positive cases and deaths in Delhi-NCR.

In this article, we examined the electrical characteristic of proposed new device structure, Wrapped Channel Field Effect Transistor (WCFET). Results of WCFET have been analyzed using Atlas 3-D simulator. WCFET shows better transfer characteristics with ON-current ION of ~10-6A and leakage current IOFF of ~10-16 A. Optimization of device characteristics has done with doping concentration (ND), gate work function (ΦG) and spacer dielectric. Impact of gate length and semiconductor film thickness variation on drain current, subthreshold slope (SS) and DIBL are also investigated. Further, effects of various gate dielectric materials such as SiO2, Si3N3, HfO2 and TiO2 are examined w.r.t. switching characteristics of WCFET. To validate of device compatibility with power supply scaling, we inspected full range variation of VDS ≈ (0.05V-to-0.7V) on transfer characteristics.

It has been observed that a sudden spurt in the number of COVID positive cases reported in the November 2020. The state government has started taking measure to prevent the spread of pandemic and to avert any probable fresh wave of COVID-19 as observed in some European countries. Moreover, winters are setting up in the northern regions of the country including Haryana which is argued as favorable condition for spread of the pandemic by some researchers. Ample data on COVID is now available about the pattern of spread of COVID-19 in the country as almost nine months have elapsed since the first positive COVID case was detected in India. This paper is designed to analyze the data based on district Gurugram of Haryana, COVID’s carriers effectiveness of the measures taken by the government, till now, to contain the spread of pandemic may also be inferred upon by the observations during this work. Finally, the significance of apprehension regarding onset of fresh wave of COVID may be predicted though the model. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

BackgroundThe COVID-19 pandemic is atypical in scale, perseverance, and geographical progression throughout the world in recent history. It is declared a public calamity in India wherein the Prime Minister’s Office is directly associated with every aspect of surveillance, control, and relief measures. This paper aims to present the digital response framework for management, surveillance, and control of the COVID-19 crisis across the country. The paper also presents technological adoption by various states and union territories and analysis of COVID cases in India. MethodsThe Ministry of Home Affairs and its various organizations such as the National Disaster Management Authority, and Ministry of Health and Family Welfare are managing various authoritative and administrative activities, and Ministry of Electronics & Information Technology through National Informatics Centre (NIC) are providing technological solution to manage the COVID-19 pandemic in India. The NIC is playing a crucial role to develop and manage digital solutions for surveillance and control of COVID-19 in India. ResultsOn analysis of COVID-19 data of reported confirmed, recovered, and deceased cases across India in various states, it is observed that Maharashtra was most affected followed by Karnataka , Kerala , Delhi and other states. ConclusionThe technological solutions developed, implemented, managed by NIC making up the digital response framework for monitoring, surveillance, and control of COVID-19 are standard for India and proved to be effective in combating the COVID-19 pandemic and are widely used in central, state, and local governing bodies.

The unprecedented advancement of technologies can reduce overall costs for the management and prevention of chronic disease. Genomic information is being integrated into Electronic Health Record, to keep reliable information in the hands of health professionals and genome experts in time to support clinical decisions for better prognosis. The Electronic Health Record is an indispensable component of health professionals’ workflow. There are innumerable hurdles that prevent the effective use of EHR and genomic data for the use of personalized medicine in health care to improve outcomes. This paper explains the association of EHR and genomic data in healthcare towards the comprehension of personalized medicine with IoT. The paper discuss the storage of genome sequencing of an individual with EHR, as the health practitioner can better diagnose irregularities in the patient's health, thus recommend an unambiguous prediction.

Traffic congestion is one of the major challenges in smart cities due to rapid urbanization. In this paper, we study the problem of traffic congestion prediction in smart city transportation systems. While there are various methods to tackle this problem, most of them suffer from improper label generation. Therefore, motivated by such shortcomings, we propose an intuitive and logical solution where we consider several road-related factors for the effective prediction of traffic congestion. For the same, we consider two datasets from the CityPulse EU FP7 project and employed two well-known binary classifiers. Our results indicate that labels generated based on the hybridization of the average speed of vehicles and the number of vehicles plying on the road prove to be effective in properly discriminating congestion and non-congestion scenarios. Moreover, number of vehicles alone can produce significant discrimination as well. Furthermore, the cumulative distribution function (CDF) applied to the above-mentioned factors with respect to the labels generated also validates the effectiveness of our approach.

The technique of finding the optimal processing method to answer a query is called Query optimization, whereas a collection of various sites, distributed over a computer network is called Distributed Database. In Distributed Database, the site communicates with each other through networks. There are various issues arise during evaluation of query cost, among which the processing cost and a transmission cost are important. There are several algorithms developed to find the best possible solution for a particular query, but they all have their certain limitations. The optimizer is mainly concern on search space, search strategy, and the cost model. It primarily focuses on these three factors. The mining cost of a query depends on the order of evaluation of the operators, for the same query we can have different cost if the order is changed. Hence, to find the optimal cost for a particular query is emerging as an open challenge for many researchers. Therefore, the cost-based query optimization technique has emerged as an important concept for dealing with the query optimization. This paper explores the issues and challenges of query optimization in mining of distributed data.

This paper explores the various code smells or the so called bad code symptoms present in procedural C software. The code smells are analyzed in the light of aspect oriented programming. The intention is to handle the code smells with aspect oriented constructs as it offers more versatile decomposition techniques than the traditional modularization techniques, for software evolution and understandability. The code smells are described at the function and program level. The code smells are followed by the aspect oriented transformations that may be required in order to improve the code quality.

The emergence of semantic web will result in an enormous amount of knowledge base resources on the web. The efficient use of knowledge resource totally depends on internet search engines which do not only help organization who are involved in the development of web browsers but also international economy as a whole buy facilitating efficient transition, managing and sending appropriate results to the web browser user. It is observed that data flowing from internet is often vague and therefore there is need to develop technology which has to get relevant and focused information. The Knowledge base grid in semantic web is an important instrument to enhance the application domain of semantic web. using the semantic web technologies for the solution of the problems of the students in the knowledge based grid distributed environment is major challenging task where they can collect coordinate publish and share knowledge to get the the admission in the course according to their ability. they can get knowledge about different universities, colleges and institutions in the distributed environment within these they select different courses according to their ability for decision making for their career and also find jobs available in the different colleges, universities and institutions in the distributed environment.

The International Workshop on Developing Tools as Plug-Ins (TOPI) is a venue for researchers and practitioners interested in plug-in development. The main interest is understanding the opportunities and challenges of developing tools as plug-ins, and thus, we seek for discussions regarding the characteristics of good plug-ins, interoperability requirements to making tools available across platforms, recent successful tools as plug-ins as well as foreseen medium and long term challenges of tools as plug-ins. The second edition of this workshop, TOPI 2012 was co-located with the International Conference on Software Engineering (ICSE 2012). TOPI 2012 received a total of 32 submissions. Among them, 14 were accepted as full papers and 4 as short papers. The audience during the whole workshop ranged from 25 to 30 participants. The final program comprised position papers including new proposals for plug-in architectures as well as their interaction with development environments and run-times, and papers discussing the implementation of different kind of tools as plug-ins. This report describes the main results of TOPI 2012.

paper, we present a three-layered predictor, Profinder, for identification and analysis of protein enzyme "Protease". This predictor is shaped by collecting the protease family domains represented by multiple sequence alignments and hidden morkov modeling techniques. Present study here is an attempt to develop a specific algorithm for searching particular domains in the genome sequences of these protein enzymes. Therefore, it is important for both basic research and drug discovery to consider the following two problems. Given the sequence of a protein, determine whether the protein is a protease or not? And if so, then which class of proteases? It is only on the basis of their sequence analysis, one can identify their types and also can predict their secondary or tertiary structures. User can test their sequences in fasta format for identification of proteases domain and therefore can get some insights on their fuctions and secondary structures. Besides, analysis based on phylogenetic relation of these proteases by constructing their phylogenetic trees in the light of evolution can be done. Storing all the information extracted from these sequences in a new database is another perspective of this present in-silico study.

systems are vital to an organization, and sometimes form the backbone of an organization, yet their maintenance and evolution had been an area of research for a long time. Besides being costly to maintain, legacy systems often lag behind changes in the businesses they support. The challenge in today's environment is to keep evolving the older systems so that they are compatible with the real world technological environment. The most common approach was to migrate the legacy code to object oriented code. However, there are many other paradigms that a legacy system might adopt. Aspect-oriented technology is another emerging programming paradigm that is receiving considerable attention from research and practitioner communities alike. Nowadays much of the work is carried on, on developing different methodologies to enable aspect oriented programming to be applied to legacy systems. In this paper, we begin by highlighting the work done in evolving a legacy system using the object oriented approach, then we analyze the impact of object oriented technology and aspect oriented technology on legacy systems and the environment that is required to implement the two paradigms. The advantages and disadvantages of both the paradigms have been explored, and a comparative study of both the paradigms is done and analyzed in the light of legacy systems.

Refactoring has become a well-known technique for improving the code in a way that preserves behavior. The application of refactorings during development process of an object oriented or procedure oriented software improves the design and therefore the quality of software. During the evolution of software it is a requirement to refactor them in order to make it more compatible and flexible with the new environment. Much work is being done in refactoring object oriented code with aspect oriented programming. But this paper describes the various types of refactoring being done on procedural codes for eg: C language and the utility of refactoring the procedural codes with the help of aspect oriented programming. The paper also proposes certain refactorings that could be achieved in a better way using AOP.

Importance of monsoon depressions, Low Pressure Systems (LPS) and the number of LPS days on rainfall and hence indirectly on agriculture and hydrology, is well recognized. In this paper the pattern of annual variability in these systems have been examined using data from 1901-2000. The above mentioned parameters have been subjected to decadal analysis to detect presence of any regular pattern. An attempt has been made to find its tendency with time. Impact of these systems on central India rainfall has been determined and discussed. The study endorses the earlier findings that there is a decreasing trend in the frequency of depressions which has been compensated with increase in LPS days over Indian region in recent years. The rainfall over central India is more significantly related with a number of LPS days over Indian region.

Extensive experimental study is carried out to investigate spectral behavior of spatially polychromatic coherent light diffracted by an annular aperture. It is found that the spectrum at the observation plane exhibits anomalous behavior after passing through the annular aperture. Experimental observations show that at a particular diffraction angle, the diffracted spectrum splits into two halves, while at other diffraction angles the spectrum either shifts towards lower wavelengths (blue-shift) or shifts towards higher wavelengths (red-shift). These spectral changes take place in the vicinity of the dark ring of the Airy pattern. Moreover, the behavior of the spectrum in the Fraunhofer region around a small circular loop centered at a critical direction is also studied and it is found that these spectral changes are qualitatively different from the spectral changes of the spectrum of the focused waves on a circle centered at the singular point. It is discussed in detail that such spectral anomalies of spatially coherent light may be exploited for information encoding and information hiding for free-space communications. The possibility to entangle bits in the spectral anomalies is also proposed. Such technique might be very useful to improve the throughput of information transmission in free space.

An understanding towards genetics and epigenetics is essential to cope up with the paradigm shift which is underway. Personalized medicine and gene therapy will confluence the days to come. This review highlights traditional approaches as well as current advancements in the analysis of the gene expression data from cancer perspective. Due to improvements in biometric instrumentation and automation, it has become easier to collect a lot of experimental data in molecular biology. Analysis of such data is extremely important as it leads to knowledge discovery that can be validated by experiments. Previously, the diagnosis of complex genetic diseases has conventionally been done based on the non-molecular characteristics like kind of tumor tissue, pathological characteristics, and clinical phase. The microarray data can be well accounted for high dimensional space and noise. Same were the reasons for ineffective and imprecise results. Several machine learning and data mining techniques are presently applied for identifying cancer using gene expression data. While differences in efficiency do exist, none of the well-established approaches is uniformly superior to others. The quality of algorithm is important, but is not in itself a guarantee of the quality of a specific data analysis.

Experimental observations of a study conducted to investigate spectral shifting and spectral switching that take place in Young's double-slit experiment with partially coherent light are reported. It is shown that for certain critical distances in the near zone of the double slit, the phenomenon of spectral switching is observed, while for other situations a spectral shift is observed. These results are consistent with a theoretical study by Pan and Lu (2001 IEEE J. Quantum Electron. 37 1377; 2002 J. Opt. A: Pure Appl. Opt. 4 349).

Multimedia database can be define as a collection of storage and retrieval systems, in which large amount of media objects are created, modified, searched and retrieved, where as Multimedia is the combination of text, image, graphics, animations, audio and video. The extension of database application to handle multimedia objects requires synchronization of multiple media data streams. Multimedia data mining refers to the extraction of implicit knowledge, data relationships, or other patterns which are not stored in multimedia files explicitly. The system's overall performance in retrieval can be increase by indexing and classification of multimedia data with efficient information fusion of the different modalities is mandatory. Apart from text retrieval, the current waves in web searching and multimedia data retrieval are the search for and delivery of 3D scenes, images, music and video. The content-based multimedia information retrieval provides new techniques and methods for searching various multimedia databases over the world.

Digital audio watermarking technique is a process of embedding perceptually transparent digital information into an original audio signal. Watermarking can be fragile or non fragile depends upon the user's requirements. The main concern of digital watermarking is to prove ownership as well as protection of the embedded information. This paper gives brief overview of existing audio watermarking techniques, their applications and future prospects of digital watermarking.

Acknowledging the successful sequencing of the human genome and the valuable insights it has rendered, genetic drafting of non-human organisms can further enhance the understanding of modern biology. The price of sequencing technology has plummeted with time, and there is a noticeable enhancement in its implementation and recurrent usage. Sequenced genome information can be contained in a microarray chip, and then processed by a computer system for inferring analytics and predictions. Specifically, smart cards have been significantly applicable to assimilate and retrieve complex data, with ease and implicit mobility. Herein, we propose "The G-Card", a development with respect to the prevalent smart card, and an extension to the Electronic Health Record (EHR), that will hold the genome sequence of an individual, so that the medical practitioner can better investigate irregularities in a patient?s health and hence recommend a precise prognosis.

Various algorithms have been devised to mathematically model the dynamic mechanism of the gene expression data. Gillespie’s stochastic simulation (GSSA) has been exceptionally primal for chemical reaction synthesis with future ameliorations. Several other mathematical techniques such as differential equations, thermodynamic models and Boolean models have been implemented to optimally and effectively represent the gene functioning. We present a novel mathematical framework of gene expression, undertaking the mathematical modeling of the transcription and translation phases, which is a detour from conventional modeling approaches. These subprocesses are inherent to every gene expression, which is implicitly an experimental outcome. As we foresee, there can be modeled a generality about some basal translation or transcription values that correspond to a particular assay.

As we are aware that for fulfilling the dream of an intelligent web, an Ontology may act as a backbone and it's significance may not be denied for realizing the vision of semantic web to add semantics or computer understandable data to the existing human readable web inorder to facilitate a more efficient knowledge use or reuse on a sharable basis on web. It means that Ontology enables to structure and conceptualize the shared knowledge of a particular domain on web but the major challenging problem is the huge decentralized nature of web which does not permit to have a single large ontology but left with the possibility of having several smaller ontologies which are difficult to implement and manage. Now, Ontology has several critical aspects where Ontology design and development is one of the fundamental key issues which may be best realized with the help of a case study. In this paper, a case study of a “Sports Complex Ontology” is presented using ontology editor SWOOP 2.3 Beta 4 presenting Ontology Statistics with some results or observations. What makes it different from others is it's key aspects which include: design criteria pictorial representation along with the key steps and it's relevance with research issues like Semantic Search patterns based on "Structure", the details being out of scope of this paper.

Extracting useful information from the web is the most significant issue of concern for the realization of semantic web. This may be achieved by several ways among which Web Usage Mining, Web Scrapping and Semantic Annotation plays an important role. Web mining enables to find out the relevant results from the web and is used to extract meaningful information from the discovery patterns kept back in the servers. Web usage mining is a type of web mining which mines the information of access routes/manners of users visiting the web sites. Web scraping, another technique, is a process of extracting useful information from HTML pages which may be implemented using a scripting language known as Prolog Server Pages(PSP) based on Prolog. Third, Semantic annotation is a technique which makes it possible to add semantics and a formal structure to unstructured textual documents, an important aspect in semantic information extraction which may be performed by a tool known as KIM(Knowledge Information Management). In this paper, we revisit, explore and discuss some information extraction techniques on web like web usage mining, web scrapping and semantic annotation for a better or efficient information extraction on the web illustrated with examples.

The two main characteristics of a good encryption algorithm are: Security and Speed. Usually security algorithms have to be embedded in a variety of applications like e-banking, online shopping, mails etc. So they should be fast as well as secure in different environments. In this paper, we do security v/s performance analysis of two algorithms Two fish and AES. First, we will discuss security issues of both algorithms by considering their safety factor. Then we study encryption speed of both algorithms by encrypting different type of data (text, image, audio) and analyze their performance in terms of throughput of every algorithm on different size of RAMs. The results show the relationship between performance of algorithms and size of RAM and type of data.

An integral component of the Semantic Web is the notion of an Ontology. Ontologies which are a means for conceptualizing and structuring knowledge play a key role in the realization of semantic web’s vision of incorporating the machineunderstandable data on the current human-readable web. Ontology Management involves various key issues like: Ontology creation or reuse, merging, matching or mapping etc. Due to the exceeding number and wide range of Ontologies day by day, there is a need of higher level of abstraction that enables information fusion across multiple Ontologies which is possible by merging various source Ontologies to form a new and larger Ontology which may replace the earlier ontologies. Ontologies that need to be merged may be similar in some aspects and different in others which is a major challenge for semantic web applications. Ontology merging refers to a process of taking two or more source ontologies and return a merged ontology based on the given source ontologies. There is a need to merge a set of all conceptual based information and physical merging at attribute level in all Ontologies without any redundancy and taking care of alignment and mapping factors or any other significant issues which may be time consuming or a challenging complex task. Various approaches, tools and techniques are being applied for this purpose. This paper highlights the merging process and it’s key issues and illustrates it with an example of merging two ontologies using prompt plug-in of protege

Today, Internet is a huge database which comprises of a large number of Web sites, search engines and other information. Due to the unstructured and semi structured data in the web pages, it is a challenging task for researchers to make a relevant and efficient search in warehouse of such type of database. Ontology may be a good mechanism for achieving this goal and Web Mining technique may be used to discover and extract meaningful or relevant information from the Web documents. In this paper, analysis of web usage mining has been made with the help of an example of sample data for which WebLog analyzer tool, “Web Log Expert” has been used and it has been appended with the development of an Ontology for an intelligent or efficient web and it’s relation with web usage mining. Finally, it also summarizes some other research challenges towards an intelligent machine and web environment.

The development of real life problem is not the key issue. Various information technologies available now a days. But the major issue is that to get more advantages of these technologies for academic purpose in distributed environment where faculty and students communicate with software technology rather then with individual. Knowledge Based Grid was introduced for publishing, managing, sharing and utilizing different amount of knowledge base resources on Semantic Web in distributed environment. Knowledge discovery from heterogeneous information sources available on knowledge Grid environment is a major challenging research and development issue. This paper mainly concerns all aspects of the knowledge discovery, sharing process and integrates grid data resource by ontology server for educational institutes and university in distributed environment.

Digital Right Management and copy-protection static techniques have been used to prevent unauthorized copying and illegal distribution of software products by the software publishers. Rigid licensing structure for software distribution used with most legacy systems, is becoming less popular and less useful due to increase in businesses which dependent on flexible software applications and change according to market environment. According to Business Software Alliance, software publishers lost several hundred billions USD in previous years due to copying of their products. Many defense mechanisms have been devised till date but the hobbyists or the black market leaders so called software pirates have always found a way out of it. This paper identifies the flaws in the existing defense mechanisms and examines social and technical challenges associated with handling software piracy prevention. The paper also characterized the currently used static licensing structure in software distribution along with its drawback and proposes a dynamic software licensing scheme which comprises software serial keys integrated with hardware token to provide an ethical optimal utilization of software to customer organization and initiates to stop software piracy.

The information retrieving from millions of data available on the computational resource is not a major challenge. But how to get relevant knowledge from the information through various information technologies available is the key issue and to utilize relevant knowledge outcomes from information for academic purpose in distributed environment where faculty and students communicate with software technology rather then with individual. Knowledge learning from heterogeneous information sources available on knowledge Grid environment is a challenging research and development issue. This paper mainly concerns all aspects of the knowledge discovery, learning, sharing process and integrates grid data resource by agents for educational institutes and university in distributed environment.

This paper presents a new algorithm for finding longest common subsequence from two given sequences of DNA, proteins etc of interest. We have presented a sequential algorithm, which is quite effective. Our method compares the given database sequence of DNA representing the entire/partial genetic structure of some organism (such sequences are very long), which is assumed to be stored in the database only once with a given query sequence. Although our method can be applied for protein or RNA Sequences but here we have only taken DNA Sequences. The bucket sorting method where elements are collected in buckets and then collected in some manner to get the sorted list inspires our algorithm. Our algorithm collects the index positions of the database sequence in respective buckets which becomes the input for the main algorithm. Given algorithm is quite effective as far as time complexity is concerned.

In this study we show that spectral anomalies shown by spatially coherent light on diffraction in the form of spectral shifting and spectral switching may be exploited for information encoding, information hiding and free-space communications.

In the present era of transition from Web 2.0 to an Intelligent Web 3.0, Sir Tim Berner's LEE Semantic Web layered architecture, is playing a key role for its significant layer issues where ontology is a milestone in incorporating semantics and in conceptualising shared knowledge of a particular domain or several domains. Ontology development using ontology editors is crucial which may be best realised with case studies. To endow the web itself with intelligence, the need is to provide semantic annotations search patterns on web documents of an ontology where semantic annotation attaches metadata to the documents, pointing to concepts and properties in an ontology and is the glue that ties ontologies into document spaces, via metadata where information is typically exported as text annotated with links to the ontology. Two case studies on ontology development have been presented using Protege and Swoop ontology editors. First, an extended case study of a 'Sports Complex Ontology' is presented using Protege 3.4.4 along with an ontology flowchart and using Swoop 2.3 Beta 4 Ontology Editor is presented highlighting various features like Venn diagram of class hierarchy, fly the mothership, pellet query instance search, ontology partition, adding annotation property, etc. Second, various semantic annotation search patterns based on 'pattern', 'Boolean', and 'facets' have been presented using KIM platform. Third, another case study illustration of a 'Dwarka Shopping Complex Ontology' is presented using SWOOP 2.3 Beta 4 Editor highlighting LHS and RHS of GCI, instances with and without GCI axioms, query retrieval look up, adding property, class expression table and ontology statistics.

Ontology creation using various editors like Protege and SWOOP plays a significant role in Semantic Web. In this paper, we illustrate the creation of a housing society ontology viz, 'Jawaharlal CGHS ontology' using Swoop and Protege, the most commonly used ontology editors. We are using Swoop 2.3 Beta 4 editor where super class and sub class hierarchy and instances have been presented with the query retrieval process using 'Fly the MotherShip' option in advanced tab and show the 'general concept inclusion axiom', 'class expression table' for relations in classes and subclasses. Then, the same ontology is created using Protege 3.4.4 and finally illustrates using the OWL code to obtain ontology class hierarchy subject/object relationship in Protege by executing a SPARQL query.

Cohesion measures the relative functional strength of a module and impacts the internal attribute of a function such as modularity. Modularity has become an accepted approach in every engineering discipline. The concept of modular design has considerably reduced the complexity of software design. It represents the strength of bond between the internal elements of the modules. To achieve effective modularity, design concepts like functional independence are considered to be very important. Aspect-oriented software development (AOSD) has emerged over the last decade as a paradigm for separation of concerns, which aims to increase the modularity. Therefore the presence of aspects affects the cohesiveness of a module. Like any new technology, aspect-oriented programming (AOP) was introduced to solve problems related to object-orientation (OO), and more in particular Java .It was noticed that AOP’s ideas were not necessarily tied to OO (and Java) but also to less modular paradigm like imperative programming. Moreover, several metrics have been proposed to assess aspect-oriented systems quality attributes in an object oriented context. However, not much work has been done to assess the impact of AOP on imperative style of programming (also called procedural paradigm, such as C language). Therefore, metrics are required to measure quality attributes for AOP used with imperative programming. Cohesion is considered an important software quality attribute. In this context, this paper presents an approach for measuring cohesion based on dependence analysis using control flow graphs (CFG).

Hydroxylation in the 11 alpha-position in the progesterone molecule employing immobilized spores of Aspergillus ochraceus strain No. G8 (CDRI catalogue No.) was achieved. For immobilization the activity of the spores was evaluated on a variety of matrices such as alginate beads, epoxy resin beads, polyacrylamide gel, and collagen. Spores entrapped in polyacrylamide gel were found to be the most active. Studies of various parameters, e.g. monomer content, cell loading capacity, optimum pH, temperature, and substrate concentration, were carried out on polyacrylamide gel. In polyacrylamide, the entrapped spores normal decay pattern, as indicated by loss of activity, was observed after four uses. At the end of 15 cycles, the residual activity was found to be 18% of the original. It was possible to regenerate the activity by incubating the preparation in a nutrient medium. The regenerated spores showed increasing rate of loss of activity upon recycling.