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CNT-TiO2 nanocomposite thin films were deposited on quartz glass substrates using sol-gel spin coating and tested the photocatalytic degradation of methylene blue (MB) under the irradiation of the solar spectrum. The absence of any sharp peak in the XRD pattern confirmed the amorphous nature of the films. The bandgap, Eg, decreased from 3.94 to 3.70 eV as the concentration of CNT increased from 0 to 3 mg. The FTIR peak detected at 1040 cm−1 indicated the vibrations of the chemical bond Ti–O–C. The photocatalytic degradation of MB rose up to 83% (CNT@2 mg) owing to charge carrier separation between TiO2 and CNT.

Nowadays, utility of the multi-criteria decision making (MCDM) technique in tackling real-world complex problems has risen tremendously. Even the United Nations is focusing on decision-making in order to accomplish Agenda 2030, as stated in its paragraph 48. The desire to promote sustainable development (SD) necessitates complex decision models, which could be achieved through the use of an efficient MCDM approach. Analytical Hierarchy Process (AHP) is one of the most efficient MCDM techniques that is incorporated in this study. The purpose of this work is to provide a contrasting of AHP's application that emerged between 2011 and 2022, rather than to reflect on its methodological improvements. Its application encompasses a wide range of disciplines including Renewable Energy, Sustainable manufacturing, Natural Hazards, Environmental Pollution, Landfill waste management and many others which lies explicitly or implicitly under the theme of SD. Previously, many reviews have been conducted that concentrated on a single decision topic; moreover, this review explore the comprehensive viewpoint of decision problems. As per statistical results, Middle Eastern countries such as Iran placed top in terms of applying AHP application in different sectors. GIS and fuzzy logic are the most often used approaches to incorporate AHP across all disciplines. Notably, the findings indicate that the most decision problem have selection and assessment as a major concern whereas, environmental, economical, LULC & DFR are more frequently used criteria.

A well-regarded as well as powerful method named the ‘analytic hierarchy process’ (AHP) uses mathematics and psychology for making and analysing complex decisions. This article aims to present a brief review of the consistency measure of the judgments in AHP. Judgments should not be random or illogical. Several researchers have developed different consistency measures to identify the rationality of judgments. This article summarises the consistency measures which have been proposed so far in the literature. Moreover, this paper describes briefly the functional relationships established in the literature among the well-known consistency indices. At last, some thoughtful research directions that can be helpful in further research to develop and improve the performance of AHP are provided as well.

Probably the best way to determine whether your SQL statements are properly optimized is by using the Oracle SQL Trace facility and the EXPLAIN PLAN command. You can use the SQL Trace facility and the Oracle program TKPROF, which is used to translate trace files, to trace production SQL statements, and gather statistics about those statements. You use SQL Trace to gather information into a trace file; the Oracle program TKPROF formats the trace information into useful, understandable data.

Tuning your SQL statements may be one of the most important tasks you can do to improve the performance of your Oracle system. By tuning your SQL statements to be as efficient as possible, you use your system to its full potential. Some of the things you can do to improve the efficiency of your SQL statements may involve as little effort as rewriting the SQL to take advantage of some property of your database or perhaps even changing the structure of the database itself.

In a computer system, the fastest storage component is the CPU cache, followed by the system memory. I/O to disk is thousands of times slower than an access to memory. This fact is the key for why you try to make effective use of memory whenever possible and defer I/Os whenever you can. The majority of the user response time is actually spent waiting for a disk I/O to occur. By making good use of caches in memory and reducing I/O overhead, you can optimize performance. The goal is to retrieve data from memory whenever you can and to use the CPU for other activities whenever you have to wait for I/Os. This paper examines ways to optimize the performance of the system by taking advantage of caching and effective use of the system's CPUs.

The efficient use of primary memory is one of the major key for the good performance achieved from the any kind of server. The management of the various components stored in the main memory is the key challenge to get the desired throughput from an application running on the server. As we know the DBMS mostly works on client-server architecture. So the memory management for the DBMS's components stored in the main memory of the server is the critical task for a DBA. The DBA should have the knowledge of the components those are stored in main memory during runtime. This paper helps the DBA to get the detailed description of these core components of DBMS.

The efforts spent on testing are enormous due to the continuing quest for better software quality, and the ever growing complexity of software systems. The situation is aggravated by the fact that the complexity of testing tends to grow faster than the complexity of the systems being tested, in the worst case even exponentially. Whereas development and construction methods for software allow the building of ever larger and more complex systems, there is a real danger that testing methods cannot keep pace with construction, hence these new systems cannot be sufficiently fast and thoroughly be tested. This may seriously hamper the development of future generations of software systems. One of the new technologies to meet the challenges imposed on software testing is model-based testing. Models can be utilized in many ways throughout the product life-cycle, including: improved quality of specifications, code generation, reliability analysis, and test generation. This paper will focus on the testing benefits from MBT methods and review some of the historical challenges that prevented model based testing and we also try to present the solutions that can overcome these challenges.

Mistakes create rework. Rework takes time and increases costs. The traditional software engineering methodology defines the ratio of Design:Code:Test as 40:20:40. As we can easily see that 40% time and efforts are used in testing phase in traditional approach, that means we have to perform rework again if we found some bugs in testing phase. This rework is being performed after Design and code phase. This rework will increase the cost exponentially. The cleanroom software engineering methodology controls the exponential growth in cost by removing this rework. It says that "do the work correct in first attempt and move to next phase after getting the proof of correctness". This new approach minimized the rework and reduces the cost in the exponential ratio. Due to the removal of testing phase, the COCOMO (COst COnstructive MOdel) used for the traditional engineering is not directly applicable in cleanroom software engineering. The traditional cost drivers used for traditional COCOMO needs to be revised. We have proposed the Extended version of COCOMO (i.e. E-COCOMO) in which we have incorporated some new cost drivers. This paper explains the proposed E-COCOMO and the detailed description of proposed new cost driver.

In today's world, web is considered as ocean of data and information (like text, videos, multimedia etc.) consisting of millions and millions of web pages in which web pages are linked with each other like a tree. It is often argued that, especially considering the dynamic of the internet, too much time has passed since the scientific work on PageRank, as that it still could be the basis for the ranking methods of the Google search engine. There is no doubt that within the past years most likely many changes, adjustments and modifications regarding the ranking methods of Google have taken place, but PageRank was absolutely crucial for Google's success, so that at least the fundamental concept behind PageRank should still be constitutive. This paper describes the components which affects the ranking of the web pages and helps in increasing the popularity of web site. By adapting these factors website developers can increase their site's page rank and within the PageRank concept, considering the rank of a document is given by the rank of those documents which link to it. Their rank again is given by the rank of documents which link to them. The PageRank of a document is always determined recursively by the PageRank of other documents.

Database administrators should be aware of resource usages to maintain database system performance. As database applications become more complex and diverse, managing database systems becomes too costly and prone to error. Autonomic database tuning becomes more important than ever. One of the major issues to address in regards to ORACLE database performance is the size of the database. The bulk of the information consists of a large number of records, contained in many tables, each ranging from thousands of rows. There are many factors that can have direct effects on the performance of the database. CPU, Memory, Network, Disk I/O are among other factors. In order to make a database up and run efficiently, each factor must be addresses carefully, and the best tuning strategy must be applied for optimum performance. ORACLE performance issues are complex, and for a DBA, there is a large number of values to monitor and examine in order to decide on best tuning strategy. The aim of the work behind this paper was to design and implement a Database Performance Tuning Measurement Toolkit for ORACLE Database Servers working on MS-Windows platforms. This system is called ARH_Db_Tuner*. This system is the advance version of ORACLE Performance Monitoring Toolkit [19] (OPMT for short). Some of the future aspects of OPMT have been implemented in ARH_Db_Tuner. It is used for testing, analysis and reporting of the database performance.

In present scenario the manual work (Done by Human) cost more to an organization than the automatic work ( Done by Machine)and the ratio is increasing day by day as per the tremendous increment in Machine (Hardware + Software) Intelligence. We are moving towards the world where the Machines will be able to perform better than today by their own intelligence. They will adjust themselves as per the customer’s performance need. But to make this dream true, lots of human efforts (Theoretical and Practical) are needed to increase the capability of Machines to take their own decision and make the future free from manual work and reduce the working cost. Our life is covered with the different types of systems working around. The information system is one of them. All businesses are having the base by this system. So there is the most preference job of the IT researcher to make the Information system self-Manageable. The Development of well-established frameworks are needed to made them Auto-tuned is the basic need of the current business. The DBMS vendors are also providing the Auto-Tune packages with their DBMS Application. But they charge for these Auto-Tune packages. This extra cost of packages can be eliminated by using some basic Operating system utilities (e.g. VB Script, Task Scheduler, Batch Files, and Graphical Utility etc.). We have designed a working framework for Automatic Tuning of DBMS by using the Basic Utilities of Operating System (e.g. Windows) .These utilities will collect the statistics of SGA dynamic Parameters. The Framework will automatically analyze these SGA Parameter statistics and give suggestions fordiagnose the problem. In this paper we have presented that framework with practical Implementation.

Business Data always growth from kilo byte, mega byte, giga byte, tera byte, peta byte, and so far. There is no way to avoid this increasing rate of data till business still running. Because of this issue, database tuning be critical part of a information system. Tuning a database in a cost-effective manner is a growing challenge. The total cost of ownership (TCO) of information technology needs to be significantly reduced by minimizing people costs. In fact, mistakes in operations and administration of information systems are the single most reasons for system outage and unacceptable performance [3]. One way of addressing the challenge of total cost of ownership is by making information systems more self-managing. A particularly difficult piece of the ambitious vision of making database systems self-managing is the automation of database performance tuning. In this paper, we will explain the progress made thus far on this important problem. Specifically, we will propose the architecture and Algorithm for this problem.

Modern data analysis applications are driven by the Network databases. They are pushing traditional database and data warehousing technologies beyond their limits due to their massively increasing data volumes and demands for low latency. There are three major challenges in working with network databases: interoperability due to heterogeneous data repositories, proactively due to autonomy of data sources and high efficiency to meet the application demand. This paper provides the two ways to meet the third challenge of network databases. This goal can be achieved by network database administrator with the usage of PL/SQL blocks and bind variable. The paper will explain the effect of PL/SQL block and bind variable on Network database efficiency to meet the modern data analysis application demand.