MS SQL Server

This research work represents an online working website of laundry containing a management system and payment gateway. Many of the laundry firms don't have a proper management system to store the records, which include many problems such as, mixing up customer's clothes or sometimes losing up the record register. This system helps the users to have to keep track of their requests/orders, they can also set drop off time at their convenience. Two login portals will be there one for admin and one for users. User portal will be used by the customers to make orders whereas from the admin portal admin can see all the users' information and the status of the orders. Rates of laundry can be changed by the admin from the admin portal according to market price, occasionally the discounts/offers will also be provided. As the payment gateway is also included on the website customers can use that for making payments. Each customer is assigned with a unique ID on registration to avoid contrasting information and their rest information is kept safe. The technical skills include PHP/NodeJS, mongoDB/MySQL, Python, HTML, CSS & JavaScript. This solution solves many problems and brings ease to operating the business. All the customers' information is managed properly as well as their service requests/orders and record of the orders can never be lost. The design of the website is also unique and has a user friendly interface. Therefore, it will also be fun for the users to interact with the website and providers of the service have an opportunity to run the business smoothly.

In the era of big data, the optimization of machine learning models within cloud-based data warehousing systems has emerged as a critical domain of research and application. This paper presents an in-depth analysis of advanced data science techniques aimed at enhancing the performance and scalability of machine learning models in such environments. Cloud-based data warehousing systems offer substantial advantages, including scalability, flexibility, and the ability to handle vast amounts of data, yet they also introduce unique challenges related to model optimization. Model selection, hyperparameter tuning, and deployment strategies are pivotal aspects of optimizing machine learning models in these contexts. The paper begins by exploring model selection techniques tailored for cloud-based systems, emphasizing the need for models that not only perform well in theory but also scale efficiently with large datasets and distributed computing resources. The selection process involves evaluating various algorithms and architectures, including ensemble methods, deep learning models, and emerging techniques such as transformer-based architectures, considering their suitability for the specific requirements of cloud environments. Hyperparameter tuning represents another critical area of focus. The paper delves into advanced methods for hyperparameter optimization, including grid search, random search, and more sophisticated approaches such as Bayesian optimization and genetic algorithms.

This article dives into the exciting transformation that Artificial Intelligence (AI) brings to data engineering and integration processes within cloud computing environments. It showcases the groundbreaking implementation of AI-driven solutions across various dimensions, such as automated pipeline generation, intelligent schema matching, anomaly detection, and real-time data integration. Using a dynamic mixed-methods approach that combines both quantitative and qualitative analyses, the article reveals astonishing improvements in data processing efficiency, with organizations experiencing up to a 67% reduction in processing time and an incredible 89% boost in accuracy. Featuring compelling case studies from the financial services, healthcare, and e-commerce sectors, the article provides compelling evidence that these innovative systems far surpass traditional methods in cost efficiency, scalability, and data quality management, all while slashing operational overhead. It also tackles the hurdles of implementation, including the integration of legacy systems and the complexities of initial deployment, offering valuable strategic insights for organizations eager to embrace AI in their data engineering workflows. This article contributes to a deeper understanding of how AI technologies can be harnessed to tackle the escalating challenges of data management in cloud computing environments, while laying the groundwork for future advancements in this fast-paced and ever-evolving field.

This documentation is been made for AMC hospital information system.
AMC hospital information system is been made in order to support the AMC hospital on data transaction and on the management of data information the hospital will contain.

By reading this documentation you will be introduced and it will represented to you the analysis, design, implementation and development phase of AMC hospital information system. All the phases of analysis, design, implementation and development are fully explained and detailed. Exceptional phases, such as technical guide which is based on the completely installation of the information system and user guide which is based on the learning of how this information system will be used, are included in this documentation fully detailed and explained.

Günümüzde aynı pazarda bulunan çeşitlilik ve marka sayısı artmıştır. Buna neden olarak gelişen dünyada girişimciliğin hayatımızda daha önemli bir rol oynaması ve bilişim teknolojileri altyapısının gelişmesi önemli etkenlerdir. Bu yoğun pazarda kendini göstermek ve müşteriye daha kolay daha hızlı ulaşmak için işletmeler sürekli yeni yollar aramıştır. Son yirmi yılda, World Wide Web (WWW), daha yaygın adıyla web, hayatımız ve işlerimiz üzerinde büyük ve kaçınılmaz bir etki bırakarak değiştirmiştir (Al-Rousan, Sulaiman, & Salam, 2009). Web 2.0 ardından web siteleri bu arayış içerisinde önemli bir paydaya sahiptir. Fakat İnternet sitelerinin interaktif bir ortam yaratması için gerekli olan dizayn esasları dikkate alınmalıdır. Etkili bir şekilde dizayn edilmemiş olan internet sitelerinin şirkete avantajlar sağlaması beklenmemelidir (İnan & Südaş, 2009). İçeriğine sadık olmayan web siteleri verimliliğini kaybeder ve pazarda daha da gerilemesine neden olur. İçeriğine sadık olup müşterinin beklentilerini karşılayan işletmeler web siteleri vasıtasıyla müşterilerine daha hızlı ulaşıp pazarda öne çıkmayı başarmıştır. Bir web sitesi projesinde planlama için kullanılan 2 adet yöntem vardır bunlar Waterfall ve Agile yöntemleridir. Bu araştırmada sanal bir otel işletmesinin web sitesi proje planlama aşamaları yapılmaya çalışılmıştır.

Pesquisa realizada no âmbito do projeto "História social da ciência e da formação científica no Brasil (1951-2011): um estudo prosopográfico", desenvolvido no Museu de Astronomia e Ciências Afins (MAST), sob coordenação de Heloisa Maria Bertol Domingues. O objetivo da pesquisa era levantar nomes e traçar trajetórias científicas de pesquisadores que receberam subsídios financeiros (bolsas e auxílios) do Conselho Nacional de Pesquisas (CNPq).

This study compares the storage needs and runtime performance of SQL-based systems with various indexing strategies, including None, Clustered, Non-Clustered, and Both. It focuses on integer and string data types. The results show that integer data typically has lower storage requirements and runs faster, whereas string data has a higher storage overhead. When it comes to string data in particular, the "Both" indexing strategy—which combines Clustered and Non-Clustered—offers efficient data retrieval but uses the most storage space. When compared to SQL indexing, Python-based systems may provide more versatile in-memory data management, which could optimize specific operations without using as much disk space. Nevertheless, SQL's indexing features make it superior for sophisticated queries on big datasets. Insights into the benefits and drawbacks of SQL-based indexing are offered by this analysis, which helps in making application-specific decisions about data storage and access.

The paper discusses the critical decision-making in choosing between SQL and NoSQL databases for FinTech applications. FinTech, founded on large-scale data processing, transactional integrity, and real-time analytics,
warrants robust and highly scalable database solutions. SQL databases are very suitable for applications such as payment processing, customer relationship management, and core banking systems because of their strong consistency, reliability, and mature ecosystem. On the other hand, NoSQL databases offer flexibility in handling unstructured data, horizontal scalability, and high availability for big data analytics, real-time fraud detection, and personalized finance services. The paper contrasts SQL and NoSQL databases concerning data structure, scalability, consistency, and availability statements of strengths and limitations in FinTech. We provide insights into which database type would be more applicable for specific FinTech applications through several practical use cases and performance evaluations. The analysis describes that SQL databases are very relevant in cases with high transactional integrity within the application or system and structured data management. In contrast, a NoSQL database would find an application in scenarios requiring flexibility and scalability with diverse data types. FinTech companies, thereby, have to think very carefully about individual needs and options to choose the right database technology, ensuring it aligns with operational requirements and strategies for future growth.

The integration of SQL and Python in machine learning workflows within cloud environments offers a robust solution to the challenges of big data analytics. This study explores the synergistic capabilities of SQL for efficient data extraction and Python for flexible data transformation, model development, and visualization. Utilizing cloud platforms such as AWS and Google Cloud, the research established scalable pipelines for processing large datasets, training machine learning models, and deploying them in real-time. Statistical analyses validated the reliability and accuracy of models, with Neural Networks achieving the highest performance metrics. Resource utilization tests highlighted the critical role of GPUs in accelerating computations, while scalability tests demonstrated the adaptability of the pipeline to varying data loads. The results underscore the cost-effectiveness and efficiency of integrating SQL and Python in cloud-based machine learning, offering valuable insights for businesses and researchers aiming to optimize big data workflows. This study provides a practical foundation for leveraging cloud technologies to enhance analytics capabilities and addresses future directions for tool integration and emerging technologies.

This study explores the optimization of hybrid cloud database architectures by integrating SQL Server and MongoDB within Azure environments, focusing on the specific benefits and challenges of such an approach. Hybrid cloud architectures are increasingly adopted by organizations seeking flexibility, scalability, and improved data management. By examining the integration of SQL Server's relational database structure with MongoDB's NoSQL capabilities, this study aims to demonstrate how businesses can achieve efficient data synchronization, enhanced security, and improved performance within the Azure cloud platform. Through a comprehensive review of existing literature, analysis of case studies, and discussion of best practices, this paper provides actionable insights for organizations considering hybrid database solutions. Key findings indicate that optimizing hybrid cloud architectures with SQL Server and MongoDB can offer substantial benefits for diverse applications, but also presents unique challenges that must be managed through strategic planning and robust architecture design. This research draws on studies and publications from U.S. journals to provide a contemporary perspective on hybrid cloud database optimization.

Dette prosjektet ble gjennomført av NIVA for Dalnave Navigation Inc., Avena Shipping Co. Ltd og Assuranceforeningen Gard-gjensidig og har omfattet miljøundersøkelser av vraket av lasteskipet MS Server som sank utenfor Fedje i 2007. Nasjonal kontakt har også vaert Wikborg Rein & Co Advokatfirma DA. I forbindelse med den pågående rettsprosessen ble NIVA engasjert for å gjennomføre miljøundersøkelser ved vraket. NIVA er en sentral aktør innen nasjonal miljøovervåkning (bl.a. i Statlig program for forurensningsovervåkning, Økosystemovervåkning i kystvann) og vi er ansvarlige for flere pågående og tidligere gjennomførte programmer som har spesiell relevans for undersøkelsene av MS Server, bl..a Kystovervåkningen, Program for lange overvåkningstidsserier, Sukkertareovervåkningen, ØKOKYST og Program for miljøgifter i norske kystområder. Data fra disse programmene representerer et solid sammenligningsgrunnlag som er brukt for å analysere funnene ved vraket av MS Server i forhold til hvordan miljøet generelt er i området, f. eks. forekomst og variasjon i det naturlige biomangfoldet og generell kunnskap om nivåer av miljøgifter. Både Gard-gjensidig og The International Tanker Owners Pollution Federation (ITOPF) deltok i sentrale deler av feltarbeidet som observatører. NIVA ønsker å takke Alex Hunt ITOPF for hjelp i forbindelse med feltarbeid og nyttige diskusjoner i forbindelse med valg av stasjonsplassering. Vi retter også en takk til IMC Diving for hjelp med å finne og skrape bunnstoff fra skroget.

The importance of the process of restoring a database requires precise examination of all factors that affect it. Considering the decline of the price of SSD and its better read and write speeds, it seems that this is the logical choice when reducing downtime is a primary concern for the organisation. This paper categorizes storage devices in use as well as main backup types in MS SQL Server. Tests are conducted to evaluate the impact of the storage device on backup and restore efficiency. In this regard, the purpose of the research is to examine problems associated with selection of a storage device for efficient backup and restore in MS SQL Server. The conducted tests showed some surprising results regarding SSD's efficiency. The reason these findings are important is that they could be used as a guideline for choosing proper storage device for an organisation's needs. 1. Introduction. The volume of data worldwide is growing enormously, hence the need for storage capacity is increasing. Over five years, the generated data has more than tripled-from 12 ZB for 2014 to the

The importance of the process of restoring a database requires precise examination of all factors that affect it. Considering the decline of the price of SSD and its better read and write speeds, it seems that this is the logical choice when reducing downtime is a primary concern for the organization. This paper categorizes storage devices in use as well as main backup types in MS SQL Server. Tests are conducted to evaluate the impact of the storage device on backup and restore efficiency. In this regard, the purpose of the research is to examine problems associated with selection of a storage device for efficient backup and restore in MS SQL Server. The conducted tests showed some surprising results regarding SSD's efficiency. The reason these findings are important is that they could be used as a guideline for choosing proper storage device for an organization's needs.

Scientific interest in the adaption in industrial domains is growing as a result of the Internet of Things' quick design and development advancements. The influence of dispersed new technologies, the topology of the industrial Internet of things, and the resource limitations associated with industrial 5.0 security are to blame. The fourth industrial revolution, known as the Industrial Internet of Things (IIoT), focuses on profits while enhancing productivity, dependability, and competitiveness. IIoTenabled technology has been studied and employed in a variety of studies, but additional investigation is needed to fully grasp the promise and challenges they present. Machine learning, or ML, helps promote the adoption of the Internet of Things (IoT) by autonomously identifying patterns in data and generating meaningful insights from massive amounts of observed data. To effectively serve governments, enterprises, and customers on their own, the Internet of Things (IoT) requires Machine Learning (ML). The Internet of Things collects environment data and employs powerful algorithms for automated human-driven decisionmaking processes. The machine learning and Internet of Things research is organised and assessed according to data, application, and industry perspectives. We review relevant studies and investigate how the Internet of Things and Artificial Intelligence (AI) may make our surroundings smarter. Our analysis includes a number of cutting-edge approaches. We also discuss distributed computing, trivial learning, deep learning, networked automobiles, managing pandemics, and the Internet of Things. Concerns about technological advances, individuals, businesses, and society as a whole surround the Internet of Things. Gaining knowledge about IoT usage can extend and enhance society's quality of life. In order to compare results of different machine learning techniques coupled with the Internet of Things, we also look at a case study.

Mayor difusión de las actividades serviciales que brinda la Microempresa. * Continuar otorgando el mejor servicio, para satisfacción de los clientes. * Consultar que herramientas debo comprar. * Consultar si el cliente quiere pagar en ese mismo instante, o por partes.

With the ever-increasing volume and complexity of data, optimizing big data processing has become paramount in the field of data management. This review paper explores the role of stored procedures in optimizing big data processing within the SQL Server environment. Stored procedures, as a crucial database programming feature, offer a sophisticated means to enhance performance, scalability, and maintainability. This paper surveys the challenges in big data processing, delves into the fundamentals of stored procedures, and provides an in-depth analysis of the advanced utilization of stored procedures for optimizing SQL Server performance. Additionally, the paper discusses related studies and research papers that contribute to the understanding and advancement of optimizing big data processing through stored procedures.

Et fiskefelt i Ytre Sklinnadjupet i Norskehavet ble i 2017 stengt for fiske av atlantisk kveite (Hippoglossus hippoglossus) på grunn av funn av høye nivåer av miljøgifter. De høye nivåene av særlig kvikksølv, men også dioksiner og PCB, kan ikke knyttes til spesielle biologiske egenskaper ved kveitene fra dette området. Det er kjent at det ble dumpet et stort antall tønner med kjemisk avfall ved Haltenbanken og Sklinnabanken fram til 1971, og det er vurdert om dette kunne være en mulig kilde. I et forsøk på å spore eventuelle kilder for miljøgifter i området, har vi i dette arbeidet analysert nivåer av miljøgifter i prøver av sedimenter og sjøpølser (Parastichopus tremulus, sedimentspisende) fra et tokt med MAREANO i juni 2018 samt i sedimentprøver fra flere tidligere tokt. Resultatene er oppsummert sammen med eksisterende kunnskap om fysisk miljø (batymetri, oseanografi, sedimentasjonsmiljø) og nivåer av kvikksølv, dioksiner og PCB i fisk fra tidligere overvåkning i og rundt området...

Laminaria hyperborea dominates the kelp zone of the outer and most wave-exposed areas of Norway, and is harvested for the production of alginate in southwestern Norway. In 1997 the Directorate of Fisheries permitted restncted kelp harvesting in the county of Sør-Trøndelag (Mid-Norway), and in 199711998 kelp was harvested within eight different areas. Research surveys including registrations of the kelp resources, regrowth after harvesting and distribution of sea urchins were carried out in 1997-1999. Large areas of kelp forest in the county of Sør-Trøndelag have previously been affected by grazing from Strongylocentrotus droebachiensis. We found high densities of S. droebachiensis and barren grounds only in the innermost and most sheltered areas. High density of kelp was found in both wave-exposed and semi-exposed areas. The average age and size of kelp plants were higher in areas with a high degree of wave exposure than in semi-exposed areas. About 0.5 year after harvesting kelp plants in regrowth populations were significantly larger in the most wave-exposed area compared to a semi-exposed one, suggesting higher growth rates in the most waveexposed areas. Echinus esculentus was observed at all exarnined stations, and could be in high densities (up to 15 specimens per m2) at semi-exposed stations. In two harvested areas east of Frøya no kelp regrowth was found 1.5 years after harvesting together with high densities of E. esculentus both in unharvested and harvested areas. At each of the examined stations the density of sea urchins was always lower in harvested areas than in unharvested kelp forest, and at the remaining harvested sites no effect of sea urchins on the regrowth of kelp was observed. At these stations the density of kelp was 2.5-8.5 kg per m2 about 1.5 years after kelp harvesting. The regrowth populations were dominated by 0-2 year-old plants. The results suggest relatively low densities of E. esculentus and high individual growth rate of kelp in the most wave-exposed parts of the area, whereas high densities of E. esculenus could be found at semi-exposed sites. As long as the current distribution and abundance of sea urchins persist in Ser-Trondelag, we recommend that kelp harvesting should be limited to the outermost and most wave-exposed areas. Most of area 2 (east of Frøya) can be characterised as semi-exposed and not suited for a sustained kelp harvesting.

Den foreliggende rapporten er utarbeidet for Molde kommune i samsvar med kontrakt av 18.6 2003. Prosjektet er gjennomført gjennom en felles innsats av flere institusjoner og mange personer. Vi vil spesielt nevne: • Avdelingssjef kommunalteknikk Tore Witsø, Molde kommune, for god kontakt og oppfølging underveis. • Merete Sundstrøm og Ann Kristin Gule ved Kystlab, Molde, for vannprøvetaking i all slags vaer og god oppfølging av analyser og oversendelse av data. • Magne Gjerstad, Molde, som på en fortreffelig måte var båtfører under vannprøvetakingen. • Merete Hestdal, Mattilsynet, Trondheim, som utarbeidet en beskrivelse av forekomsten av algegifter ved Cap Clara. Feltarbeid, artsbestemmelser og rapportering av hardbunnsundersøkelsene (kap. 6) ble gjort av Frithjof Moy og Mats Walday fra NIVA. Takk til Jan Olav Gussiås fra Molde som fungerte som reservedykker ved dykkeregistreringene. Undersøkelsen av bløtbunnsfauna ble utført med fartøyet M/B "Vakt" fra Molde havnevesen, med mannskap Ø. Nilsen, J. Stølseth og J. Indrestrand. Toktdeltakere fra NIVA var Jarle Håvardstun og Lise Tveiten. Artsbestemmelsene av mangebørstemark er gjort av Pirkko Rygg. Resultatene er rapportert av Brage Rygg (kap. 7). Birger Bjerkeng og Merete Schøyen, NIVA, har arbeidet med tilrettelegging av de vannkjemiske dataene. Erik Bjerknes og Ingar Becsan har organisert forsendelser av feltutstyr mellom Oslo og Molde. Jarle Molvaer har vurdert de vannkjemiske resultatene, har skrevet kapitlene 1-5 og 8 samt fungert som prosjektleder. Det komplette datamaterialet fra undersøkelsen blir framlagt i en egen rapport.

Data migration is the process of transferring data between data storage systems, data formats, or computer systems. This paper provides a simple application to transfer data from several databases into a single database which has been designed as a data store, by using Microsoft SQL Server. In order to collect the data in one database, so that saves and analysis the data, assess performance and improves the level of services. Using C# programming language was developed the application program which transfers from several databases to single database. The result was data transmission without problems or loss.

In this paper, we review two password schemes that use a smart card. The schemes verify the logon password without a password file. Both schemes are based on the idea of integer factoring and discrete logarithm problem. Also, we describe some schemes that indicated that there are two security problems in these password-typed smart card schemes: impersonation and offline password guessing attack. Then, we analyze the protection defenseless of the schemes. Assume that the hacker manages to calculate the modular exponentiation on both sides of the password schemes, with intercepted retrieve request, the hacker can create new access request with a successful entry into the remote server.

Tingstad, L., & Nybø, S. 2019. Radioaktiv forurensning i ville planter. Overvåking av radioaktivt cesium-137 i utvalgte områder i norsk natur. NINA Rapport 1739. Norsk institutt for naturforskning. Radioaktive stoffer fra menneskelig aktivitet som slippes ut i naturen i større mengder kan utgjøre en fare for både planter, dyr og mennesker. Etter ulykken i Tsjernobyl i 1986 fikk flere områder i Norge til dels store nedfall av radioaktivt materiale, deriblant nedfall av radioaktivt cesium (Cs-137) som har en fysisk halveringstid på 30 år. Dette nedfallet har ført til forurensning av flere områder, og grunnet den lange halveringstiden er Cs-137 fremdeles tilstede i naturen. Gjennom et overvåkingsprogram har man i utvalgte områder kunnet følge nivåene av radioaktivt cesium fra tidlig på 90-tallet og frem til i dag. Formålet med overvåking av radioaktive stoffer i naturen er å bygge opp referansekunnskap om nivåer, opptak og transport av radioaktiv forurensning i ulike arter og økosystem...

Data has been, is, and will be an important part of our lives. Today, with the advancement of technology, the amount of data produced and its importance has increased so that a wrong data stream can lead to catastrophic and even irreparable problems. These errors can be made by information thieves and hackers, intentionally, to corrupt or misuse data. In this age when data is a very sensitive commodity, attacking and destroying or losing, or even disclosing it can cause irreparable damage, and in sensitive cases such as military and political data, it can lead to the failure and even overthrow of governments. With regard to such cases, the need for data protection and security and related solutions are raised, such as data encryption and monitoring and control of data access.

This project is a Contactless RFID-based smart card railway system that includes passenger / traveler registration, bill management, testing management, and account management. This
designed system provides the facilities to easy to access, easy to handle and the interface is very
user friendly, People doesn’t want to stand in line (Que) at the railway stations. And no need
waste their time. In this system anyone would get Contactless RFID Smard Card for their
travelling purposes at the railyway stations. And they can top-up the card and can be able to pay
their travelling cost through the Smart Card after the confirmation they Payment will be deducted
from their Smart Card. This method makes the data processing very fast.

In 2007 the ranking of the top ten critical vulnerabilities for the security of a system established code injection as the top 2, closely following top 1 XSS attacks. The first release candidate of the 2010 version of the ranking has promoted code injection attacks to top 1. Actually, the most critical attacks are those that combine XSS techniques to access systems and code injection techniques to access the information. The potential damage associated with this kind of threats, the total absence of background and the fact that the solution to mitigate these vulnerabilities must be worked together with programmers, systems administrators and database vendors justifies an in-depth analysis to estimate all the possible ways of implementing this technique.

På oppdrag fra Statoil ASA, ved Odd Inge Sandvik, ble det gjennomført undersøkelser av effekter fra organotinn (TBT) på purpursnegl (Nucella lapillus) i området rundt Statoils gassterminal ved Kårstø i perioden 2.-5. juli 2002. Undersøkelsene er en del av et større overvåkingsprogram av resipienten utenfor gassterminalen. Feltarbeidet ble utført av Mats Walday, Frithjof Moy og Lise Tveiten, alle NIVA. Lise Tveiten gjorde imposexanalysene, mens Siv Hege Wang (NIVA) har vaert ansvarlig for de kjemiske analysene. Mats Walday og Lise Tveiten har forfattet rapporten.

Database backups have traditionally been used as the primary mechanism to recover from hardware and user errors. High availability solutions maintain redundant copies of data that can be used to recover from most failures except user or application errors. Database backups are neither space nor time efficient for recovering from user errors which typically occur in the recent past and affect a small portion of the database. Moreover periodic full backups impact user workload and increase storage costs. In this paper we present a scheme that can be used for both user and application error recovery starting from the current state and rewinding the database back in time using the transaction log. While we provide a consistent view of the entire database as of a point in time in the past, the actual prior versions are produced only for data that is accessed. We make the as of data accessible to arbitrary point in time queries by integrating with the database snapshot feature in Microsof...

På oppdrag fra Lillestrøm kommune og Vannområde Leira-Nitelva har vi undersøkt miljøgifter i åtte fiskearter i Nedre Nitelva, innenfor to ulike områder, i den øvre delen av vannforekomsten (strekningen Kjellerholen til Bondetangen) og i den nedre delen av vannforekomsten (strekningen fra Øya til Gullaugvika). Fisk ble fanget i garn den 24-25. august 2020. Miljøgifter som er undersøkt er polysykliske aromatiske hydrokarboner (PAH), perfluorerte alkylforbindelser (PFAS), kvikksølv og andre metaller. Asle Økelsrud og Kine Baek har i fellesskap ledet prosjektet, med ansvar for henholdsvis innsamling/rapportering og kjemiske analyser. Asle Økelsrud og Morten Jartun har samlet inn fisk, Espen Lund og Marthe Torunn Solhaug Jenssen har stått for opparbeiding av prøver og registrering av fiskemorfometridata, Kine Baek har organisert alle kjemiske analyser, og Asle Økelsrud, Morten Jartun og Sigurd Øxnevad har skrevet rapporten.

Le reti di monitoraggio strumentali, in senso lato, servono a conoscere lo stato di determinate grandezze al variare del tempo. In particolare, una rete distribuita su di un territorio è inoltre in grado di fornire misure della stessa grandezza (temperatura ad ...

This project aims to develop a system which converts a natural language statement into MySQL query to retrieve information from respective database. The system mainly focuses on creation of complex queries which includes nested queries with more than two-level depth, queries with aggregate functions, having clause, group by clause and co-related queries which are formed due to constraint on aggregate function. The natural language input statement taken from the user is passed through various OpenNLP natural language processing techniques like Tokenization, Parts of Speech Tagging, Stemming and Lemmatization to get the statement in the desired form. The statement is further processed to extract the type of query, the basic clause, which specifies the required entities from the database and the condition clause, which specifies constraints on the basic clause. The final query is generated by converting the basic and condition clauses to their query form and then concatenating the condition query to the basic query. Currently, the system works only with MySQL database.

In this research, an intelligent system is designed between the user and the database system which accepts natural language input and then converts it into an SQL query. The research focuses on incorporating complex queries along with simple queries irrespective of the database. The system accommodates aggregate functions, multiple conditions in WHERE clause, advanced clauses like ORDER BY, GROUP BY and HAVING. The system handles single sentence natural language inputs, which are with respect to selected database. The research currently concentrates on MySQL database system. The natural language statement goes through various stages of Natural Language Processing like morphological, lexical, syntactic and semantic analysis resulting in SQL query formation.

Data is a valuable resource once provided in the proper context; data becomes information to make high-quality and quick business decisions. In today's world, an important factor that drives a successful organization is gathering data that can be analyzed to gain greater insights into the business and enable new opportunities allowing the business to innovate products/services based on consumer preference. Organizations leverage data to increase customer satisfaction, maximize profitability, and deliver products and services to customers. While information has always been an important asset for an organization, it has never been as critical earlier as it is in business today. Any interruption in data accessibility, lack of adequate data security practices and data breaches can lead to serious financial and legal implications. It is not always possible for organizations to avoid disasters; however, having disaster recovery plans and effective data security strategies can help in minimizing the potential damage and can also completely avoid it. The data warehouse, or enterprise data warehouse (EDW), is an organization's core analytics system that aggregates data from different sources system into a single data warehouse to support data analysis, data mining, machine learning, and artificial intelligence (AI). Choosing a data platform that can handle massive volumes of big data, high speeds, and reliability, not to mention ease of use, is a top priority for any business as they struggle to pull the right information from their data. Snowflake is the most popular solution which supports multi-cloud infrastructure environments such as Amazon Web Services (AWS), Microsoft Azure (Azure) and Google Cloud Platform (GCP). It is a highly scalable cloud data warehouse "as-a-service", enabling users to focus on analyzing data and providing a multilayered security architecture to protect customer data with replication and failover/failback functionality. This paper aims to evaluate Snowflake's capabilities for data sharing within and outside an organization, disaster management, data security, and handling of structured and semi-structured data loads and utilize them in cloudbased reporting solutions.

Bilgisayar ve iletişim teknolojilerinin gelişimi her geçen gün daha fazla organizasyonun süreçlerini ve iş modellerini değiştirmektedir. Bu hızlı değişim, bireysel ve kurumsal açılardan, çok büyük verilerin üretildiği, bu verilerin saklanmasının, işlenmesinin ve yönetilmesinin çok önemli olduğu bir gerekliliğe yol açmaktadır. Bu bilgiler ışığında yoğun okuma yazma gibi veritabanı işlemleri yapan organizasyonlar, performans ve esneklik gibi çeşitli ölçütler nedeniyle ilişkisel veritabanı yönetim sistemleri yerine farklı veritabanı tasarımları üzerinde durmaktadırlar. Bu veritabanı sistemlerinden bir tanesi de NoSQL adını verdiğimiz veritabanlarıdır. NoSQL sağladığı özelliklerle, ortaya çıkan boşluğu doldurmuş ve uygulamada farkındalık yaratmıştır. Amazon, eBay, Linkedin vb e-ticaret ve e-iş uygulayan organizasyonlar, büyüyen verileri saklamak ve farklı hizmetlerinin doğru sunumu için NoSQL" e güvenmektedir. NoSQL veritabanları, bazı organizasyonlar tarafından kendi bünyelerinde geliştirilse bile, yaygın olarak kullanılan NoSQL veritabanları da bulunmaktadır. Bazı organizasyonlar NoSQL veritabanlarını hibrit bir yapıda ilişkisel veritabanları ile birlikte kullanmaktadır. NoSQL; yatay ölçeklendirebilme, hız, dağıtık sistemlere uygunluk, verimlilik vb. özellikler açısından fark yaratsa da, birden fazla tablo üzerinde birlikte işlem yapıldığı durumlarda sorun oluşturabilmektedir. Vurgulanan farklı yapıların özellikleri açısından, bu çalışmada, NoSQL veritabanları ile ilişkisel veritabanları karşılaştırılmalı olarak incelenmiş ve politika önerileri ortaya konulmaya çalışılmıştır.

Kegiatan yang ada pada perusahaan dagang pada umumnya yaitu pembelian dan penjualan. Selain kedua kegiatan tersebut yang terkadang hampir dilupakan namun merupakan hal vital diantara adalah kegiatan penggajian karyawan. Masalah pemberian gaji merupakan hal yang penting karena mempunyai pengaruh yang sangat besar terhadap semangat kerja para karyawannya. PD. Perkasa 3 memiliki ratusan karyawan yang berbeda sistem perhitungan penggajiannya. Kerumitan pencatatan dan perhitungan penggajian dapat diatasi dengan rancang bangun  sebuah aplikasi penggajian berbasis website yang dibangun menggunakan  framework code igniter dengan bahasa pemrograman PHP dan database MySQL mampu memecahkan masalah mengenai rumitnya pencatatan dan perhitungan penggajian pada PD. Perkasa 3. Saat ini, PD. Perkasa 3 dapat melakukan penggajian dengan cepat dan tepat, pelaporan dan pengarsipan lebih rapi, aman, tidak mudah terbakar, basah dan hilang karena data tersimpan pada database rancang bangun ini dilakukan de...

Bu çalışmada, klasik veri tabanlarında bulanık sorgulama işlemini gerçekleştiren bir “esnek sorgulama aracı” geliştirilmiştir. Esnek sorgulama işlemi, veri tabanındaki kayıtlı tablolar üzerindeki nitelik değerlerinin bulanıklaştırılması işlemi ile gerçekleştirilir. Geliştirilen ...

This article analyze aspects related to the mobile agents and security problems these entail, presenting a model access to databases that allow in a high degree to improve the response times in the network and to create a security model that collaborates with user's authentication process. The proposed model has denominated ABADAM (Access to Databases using Mobile Agents), ABADAM was implemented using: the Java programming language, API Aglets and MS-SQL Server. ABADAM offers a high level of security to protect the database server from malicious agents attacks, allowing access to the valid agents only. The security is based fundamentally on the authentication or identification process of agents that arrive to the server, this process will be able to detect non-valid agents and it will eliminate when considering them malicious agents. In addition if some ill-disposed user created a mobile agent with login and password valid will not be able to make the authentication when it will not be carrying the credential that credits it as a reliable agent and it would be destroyed immediately.

SQL Server provides a solution for mission-critical applications that require the highest levels of availability. SQL Server failover clustering is part of the SQL Server high-availability technology toolset and is designed to help businesses meet their availability and uptime goals. This provides protection against both planned as well as unplanned downtime. When a server on one of the node fails SQL Server can continue serving request through other node(s). SQL Server includes several changes to the implementation of SQL Server failover clustering, including an entirely new setup process and support for up to 16 nodes. This project discusses several new and existing concepts for SQL Server failover clustering, such as architecture, implementation, administration, and troubleshooting.

This article analyze aspects related to the mobile agents and security problems these entail, presenting a model access to databases that allow in a high degree to improve the response times in the network and to create a security model that collaborates with user's authentication process. The proposed model has denominated ABADAM (Access to Databases using Mobile Agents), ABADAM was implemented using: the Java programming language, API Aglets and MS-SQL Server. ABADAM offers a high level of security to protect the database server from malicious agents attacks, allowing access to the valid agents only. The security is based fundamentally on the authentication or identification process of agents that arrive to the server, this process will be able to detect non-valid agents and it will eliminate when considering them malicious agents. In addition if some ill-disposed user created a mobile agent with login and password valid will not be able to make the authentication when it will not be carrying the credential that credits it as a reliable agent and it would be destroyed immediately.

1,2,3Student, Department of Information Technology, Dwarkadas J. Sanghvi College of Engineering, Mumbai, India 4Assistant Professor, Department of Information Technology, Dwarkadas J. Sanghvi College of Engineering, Mumbai, India ---------------------------------------------------------------------***---------------------------------------------------------------------Abstract Automatic Database Schema Generator is a tool that facilitates schema designing from Natural language based textual requirements as an input from the user, thus, automating the process of extracting probable entities and their attributes, identifying primary and foreign keys, etc. and thereby, eliminating time consuming requirement analysis phase in the project development lifecycle. This paper proposes how Natural language based textual requirements can be analysed to extract the entities from plain text and produce a database schema. Natural language text can tend to be ambiguous due to varied contextual mea...

The data stored for a long time in livestock enterprises will play a crucial role in increasing the productivity in animal production, revealing animal breeding values, meeting qualified breeding needs, making effective breeding organizations, obtaining high income, determining the animals to be kept or as a breeder. Among the important technical data kept in livestock enterprises; ram, bull, and goat and their reproduction, growth-development, yield records (animal weight and wool yield in small ruminants, body weight gain, feed consumption, lactation and milk yield), reproductive performance measures, slaughter and carcass dimensions and characteristics records such as meat quality, animal diseases and vaccination practices can be shown as important technical data in livestock enterprises. Issues such as followed animals and storing identifying information of the animals from this data in the database are being made compulsory for conformity program of Turkey with the European Uni...