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Journal articles on the topic 'Novell software'

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Published: 4 June 2021
Last updated: 7 February 2022

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1

Nichol, Sandy. "Novell wages war on Israeli software piracy." Computers & Security 18, no. 4 (January 1999): 339. http://dx.doi.org/10.1016/s0167-4048(99)90730-7.

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2

Bigler, Mark. "A Novell Netware Version 4 Audit Program." EDPACS 24, no. 3 (September 1996): 1–7. http://dx.doi.org/10.1080/07366989609452268.

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3

Campbell-Kelly, Martin. "Not Only Microsoft: The Maturing of the Personal Computer Software Industry, 1982–1995." Business History Review 75, no. 1 (2001): 103–45. http://dx.doi.org/10.2307/3116558.

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In the thirteen years following the introduction of IBM's first personal computer in 1982, Microsoft rose from being a small concern to become the colossus of the PC software industry. However, Microsoft was not the only software company to profit from the PC-software boom: firms like AutoDesk, Lotus Development, WordPerfect Corp., Ashton-Tate, Novell, Borland, Adobe Systems, Aldus, Symantec, and the Santa Cruz Operation all had their time in the sun. Whereas some of these firms lost their markets to Microsoft or stumbled through strategic errors, others remained hugely successful, and their relative obscurity is largely due to the contemporary obsession with Microsoft and its billionaire founder.
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4

Lund, Mark W. "More Than One Ever Wanted To Know About X-ray Detectors Part IV: Windows for Elements Heavy and Light." Microscopy Today 3, no. 3 (April 1995): 3–4. http://dx.doi.org/10.1017/s155192950006315x.

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I attend a local entrepreneur's luncheon once a month. Since the small town 1 live is the home of Word Perfect Corporation, and Novell, inc. is just down the road, you can imagine that mamy members are doing exciting things with software. When I tell them that MOXTEK makes windows (or X-ray detectors they really light up, until I tell them that! mean real windows.X-ray detectors are used in electron microscopy to add chemical element analysis to the imaging capability of the microscope. A typical energy dispersive spectrometer uses a silicon crystal about the si2e of a shirt button to detect and measure the energy of incoming X-rays.
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5

Y, Dinesh Kumar, and Nuka Raju Kolli. "Novel Metrics in Software Industry." International Journal of Trend in Scientific Research and Development Volume-2, Issue-1 (December 31, 2017): 1252–58. http://dx.doi.org/10.31142/ijtsrd8215.

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6

Gharehchopogh, Farhad Soleimanian, Isa Maleki, and Seyyed Reza Khaze. "A novel particle swarm optimization approach for software effort estimation." International Journal of Academic Research 6, no. 2 (March 30, 2014): 69–76. http://dx.doi.org/10.7813/2075-4124.2014/6-2/a.12.

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7

Forgetta, Vincenzo, and J. Brent Richards. "Software Application Profiles: useful and novel software for epidemiological data analysis." International Journal of Epidemiology 45, no. 2 (April 2016): 309–10. http://dx.doi.org/10.1093/ije/dyw064.

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8

CHUANG, LI-YEH, and CHENG-HONG YANG. "A NOVEL BIOLOGICAL PATHWAYS TOOL SOFTWARE." Biomedical Engineering: Applications, Basis and Communications 17, no. 01 (February 25, 2005): 27–30. http://dx.doi.org/10.4015/s1016237205000056.

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In the research category of bio-informatics, gene interaction and biochemical reactions constitute a rather complicated sub-category. This area of research presents a big challenge for biologists. Determining biological pathways, and the complex chemical reactions involved, is very difficult. Nevertheless these research results are very valuable. Harnessing the calculating power of computer networks and freely circulating information, computer-drawn graphs can be used to express biological pathways, and thus provide biologists with a powerful tool to present their research. In this paper, JAVA programming language combined with extendable markup language is used to develop a bio-pathway drawing software tool that is connected to a gene database and gene expression analysis. Two currently available genetic pathway software tools, PathwayEdit and GenMAPP, were compared to the newly developed software. The participants involved in testing the software expressed a highly affirmative response to the new system.
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9

Seaman, Claire, and Terry Kirk. "Novel computer software for nutrition education." Health Education 96, no. 4 (August 1996): 32–34. http://dx.doi.org/10.1108/09654289610119045.

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10

Hassan, Muhammad Umair, Muhammad Umair, and Haider Ali. "Novel Approaches to Improve Software Quality." International Journal of Software Engineering and Its Applications 11, no. 6 (June 30, 2017): 15–24. http://dx.doi.org/10.14257/ijseia.2017.11.6.02.

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11

Patranabis, D., and D. Ghosh. "A novel software-based transducer linearizer." IEEE Transactions on Instrumentation and Measurement 38, no. 6 (1989): 1122–26. http://dx.doi.org/10.1109/19.46412.

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12

Stumbo, Phyllis J. "Novel software applications using nutrient databases." Journal of Food Composition and Analysis 16, no. 3 (June 2003): 293–97. http://dx.doi.org/10.1016/s0889-1575(03)00031-0.

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13

He, Rongyu, Zheng Qin, and Shaojie Wu. "A Novel Protocol for Software Authentication." Information Technology Journal 9, no. 2 (February 1, 2010): 395–98. http://dx.doi.org/10.3923/itj.2010.395.398.

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14

Asrani, Sanjay. "Novel Software Strategy for Glaucoma Diagnosis." Archives of Ophthalmology 129, no. 9 (September 1, 2011): 1205. http://dx.doi.org/10.1001/archophthalmol.2011.242.

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15

Steinbrückner, Frank, and Claus Lewerentz. "Understanding software evolution with software cities." Information Visualization 12, no. 2 (March 19, 2012): 200–216. http://dx.doi.org/10.1177/1473871612438785.

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Software cities are visualizations of software systems in the form of virtual cities. They are used as platforms to integrate a large variety of product- and process-related analysis data. Their usability, however, for real-world software development often suffers from their inability to appropriately deal with software changes. Even small structural changes can disrupt the overall structure of the city, which in turn corrupts the mental maps of its users. In this article we describe a systematic approach to utilize the city metaphor for the visualization of evolving software systems as growing software cities. The main contribution is a new layout approach which explicitly takes the development history of software systems into account. The approach has two important effects: first, it creates a stable gestalt of software cities even when the underlying software systems evolve; thus, by preserving its users’ mental maps these cities are especially suitable for use during ongoing system development. Second, it makes history directly visible in the city layouts, which allows for supporting novel analysis scenarios. We illustrate such scenarios by presenting several thematic cities’ maps, each capturing specific development history aspects.
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16

Falker, Gerrit-Milena. "Händler sollen Software aktualisieren." Lebensmittel Zeitung 73, no. 7 (2021): 26. http://dx.doi.org/10.51202/0947-7527-2021-7-026.

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17

Gautam, Pratiksha, and Hemraj Saini. "A Novel Software Protection Approach for Code Obfuscation to Enhance Software Security." International Journal of Mobile Computing and Multimedia Communications 8, no. 1 (January 2017): 34–47. http://dx.doi.org/10.4018/ijmcmc.2017010103.

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Over the past few decades ago, software developers analyzed robustly several forms of software protection against illegal copying or piracy. With the expansion in digital technology, the risk of illegal copying of software also amplifies. The increasing piracy rate has posed a serious threat to software developers leading to the development of various software protection techniques. However, various techniques have been proposed for copyright protection such as software watermarking, obfuscation, tamper-proofing and diversity. The code transformation (obfuscation) is a method of transforming a program into a form which is more complicated for an adversary to understand or change the original code from an illegitimate process of reverse engineering. None of the current code obfuscation approaches provide resistance from reverse engineering attacks. The reverse engineering threat occurs due to the unconfined software code to the user. Malicious reverse engineering of software codes can be harder by exertion of code transformation on software programs. To address this, we acquaint a peculiar code transformation approach for software protection. The proposed approach is used semantically equivalent to code clone within the source code to protect logical part of program text. We have successfully implement our approach using open source java project Gantt project system and open source java obfuscator's tools. In this paper, we present our approach and demonstrate it with an illustration. The intent of this method is to prevent static analysis attack and make dynamic attack compact for an adversary. This makes it worthwhile against reverse engineering attacks.
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18

Saputri, Theresia Ratih Dewi, and Seok-Won Lee. "Software Analysis Method for Assessing Software Sustainability." International Journal of Software Engineering and Knowledge Engineering 30, no. 01 (January 2020): 67–95. http://dx.doi.org/10.1142/s0218194020500047.

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Software sustainability evaluation has become an essential component of software engineering (SE) owing to sustainability considerations that must be incorporated into software development. Several studies have been performed to address the issues associated with sustainability concerns in the SE process. However, current practices extensively rely on participant experiences to evaluate sustainability achievement. Moreover, there exist limited quantifiable methods for supporting software sustainability evaluation. Our primary objective is to present a methodology that can assist software engineers in evaluating a software system based on well-defined sustainability metrics and measurements. We propose a novel approach that combines machine learning (ML) and software analysis methods. To simplify the application of the proposed approach, we present a semi-automated tool that supports engineers in assessing the sustainability achievement of a software system. The results of our study demonstrate that the proposed approach determines sustainability criteria and defines sustainability achievement in terms of a traceable matrix. Our theoretical evaluation and empirical study demonstrate that the proposed support tool can help engineers identify sustainability limitations in a particular feature of a software system. Our semi-automated tool can identify features that must be revised to enhance sustainability achievement.
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19

McCoy, Airlie J., Ralf W. Grosse-Kunstleve, Paul D. Adams, Martyn D. Winn, Laurent C. Storoni, and Randy J. Read. "Phasercrystallographic software." Journal of Applied Crystallography 40, no. 4 (July 13, 2007): 658–74. http://dx.doi.org/10.1107/s0021889807021206.

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Phaseris a program for phasing macromolecular crystal structures by both molecular replacement and experimental phasing methods. The novel phasing algorithms implemented inPhaserhave been developed using maximum likelihood and multivariate statistics. For molecular replacement, the new algorithms have proved to be significantly better than traditional methods in discriminating correct solutions from noise, and for single-wavelength anomalous dispersion experimental phasing, the new algorithms, which account for correlations betweenF+andF−, give better phases (lower mean phase error with respect to the phases given by the refined structure) than those that use meanFand anomalous differences ΔF. One of the design concepts ofPhaserwas that it be capable of a high degree of automation. To this end,Phaser(written in C++) can be called directly from Python, although it can also be called using traditionalCCP4keyword-style input.Phaseris a platform for future development of improved phasing methods and their release, including source code, to the crystallographic community.
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20

PANAGIOTOU, DIMITRIS, and GREGORIS MENTZAS. "LEVERAGING SOFTWARE REUSE WITH KNOWLEDGE MANAGEMENT IN SOFTWARE DEVELOPMENT." International Journal of Software Engineering and Knowledge Engineering 21, no. 05 (September 2011): 693–723. http://dx.doi.org/10.1142/s0218194011005414.

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Managing knowledge in software development is very important, since software development is a human and knowledge intensive activity. The main asset of a software organization consists of its intellectual capital. In this paper we propose KnowBench, a novel knowledge management system that integrates into the daily software development process and can be used for capturing knowledge and experience as soon as it is generated by providing lightweight tools based on Semantic Web technologies. This approach supports developers during the software development process to produce better quality software. The goal of KnowBench is to support the whole knowledge management process when developers design and implement software by supporting identification, acquisition, development, distribution, preservation, and use of knowledge — the building blocks of a knowledge management system.
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21

Viswam, Santhy, and Sajeer Karattil. "A Novel Approach for Software Requirement Specification." International Journal of Computer Applications 84, no. 17 (December 18, 2013): 14–18. http://dx.doi.org/10.5120/14677-2963.

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22

Martinov, S., T. Löbhard, T. Lunt, K. Behler, R. Drube, H. Eixenberger, A. Herrmann, et al. "Three novel software tools for ASDEX Upgrade." Fusion Engineering and Design 112 (November 2016): 839–44. http://dx.doi.org/10.1016/j.fusengdes.2016.06.034.

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23

Okutan, Ahmet, and Olcay Taner Yildiz. "A novel kernel to predict software defectiveness." Journal of Systems and Software 119 (September 2016): 109–21. http://dx.doi.org/10.1016/j.jss.2016.06.006.

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24

Kumar Yogi, Manas, G. Ku mari, Himatej S R Y, and V. S. G. Mani kanta. "Future of Software Testing: Novel Perspective, Challenges." International Journal of Computer Trends and Technology 55, no. 1 (January 25, 2018): 4–6. http://dx.doi.org/10.14445/22312803/ijctt-v55p102.

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25

Chatterjee, Subhashis, and Arunava Roy. "Novel Algorithms for Web Software Fault Prediction." Quality and Reliability Engineering International 31, no. 8 (July 8, 2014): 1517–35. http://dx.doi.org/10.1002/qre.1687.

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26

Yan, Yongquan. "Novel method to forecast software aging problems." Journal of Engineering 2019, no. 10 (October 1, 2019): 7237–43. http://dx.doi.org/10.1049/joe.2018.5407.

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27

anya, M. Sug, and K. Alagar samy. "A Novel Organizational Framework for Software Process." International Journal of Computer Science and Engineering 4, no. 6 (June 25, 2017): 49–51. http://dx.doi.org/10.14445/23488387/ijcse-v4i6p109.

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28

Yu, Jincong, Lin Shui, and Baishan Fang. "BestCodon: Novel software for codon bias analysis." Journal of Biotechnology 136 (October 2008): S349—S350. http://dx.doi.org/10.1016/j.jbiotec.2008.07.801.

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29

Cai, Kai-Yuan, Chuan-Yuan Wen, and Ming-Lian Zhang. "A novel approach to software reliability modeling." Microelectronics Reliability 33, no. 15 (December 1993): 2265–67. http://dx.doi.org/10.1016/0026-2714(93)90066-8.

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30

Schmidt, Max, Roberta Schiller, Katja Anslinger, Peter Wiegand, and Volker Weirich. "Statistefix 4.0: A novel probabilistic software tool." Forensic Science International: Genetics 55 (November 2021): 102570. http://dx.doi.org/10.1016/j.fsigen.2021.102570.

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31

Shah, Jalal, Nazri Kama, and Nur Azaliah A Bakar. "A NOVEL EFFORT ESTIMATION MODEL FOR SOFTWARE REQUIREMENT CHANGES DURING SOFTWARE DEVELOPMENT PHASE." International Journal of Software Engineering & Applications 9, no. 6 (November 30, 2018): 11–30. http://dx.doi.org/10.5121/ijsea.2018.9602.

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32

Zhu, Mengmeng, and Hoang Pham. "A Novel System Reliability Modeling of Hardware, Software, and Interactions of Hardware and Software." Mathematics 7, no. 11 (November 4, 2019): 1049. http://dx.doi.org/10.3390/math7111049.

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In the past few decades, a great number of hardware and software reliability models have been proposed to address hardware failures in hardware subsystems and software failures in software subsystems, respectively. The interactions between hardware and software subsystems are often neglected in order to simplify reliability modeling, and hence, most existing reliability models assumed hardware subsystems and software subsystem are independent of each other. However, this may not be true in reality. In this study, system failures are classified into three categories, which are hardware failures, software failures, and hardware-software interaction failures. The main contribution of our research is that we further classify hardware-software interaction failures into two groups: software-induced hardware failures and hardware-induced software failures. A Markov-based unified system reliability modeling incorporating all three categories of system failures is developed in this research, which provides a novel and practical perspective to define system failures and further improve reliability prediction accuracy. Comparison of system reliability estimation between the reliability models with and without considering hardware-software interactions is elucidated in the numerical example. The impacts on system reliability prediction as the changes of transition parameters are also illustrated by the numerical examples.
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33

Shaikh, Yasmin, and Sanjay Tanwani. "Software Evolution-based Aspect Mining: A Novel Approach." International Journal of Data Mining And Emerging Technologies 7, no. 2 (2017): 97. http://dx.doi.org/10.5958/2249-3220.2017.00013.1.

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34

Huang, Chien-Cheng, Feng-Yu Lin, Frank Yeong-Sung Lin, and Yeali S. Sun. "A novel approach to evaluate software vulnerability prioritization." Journal of Systems and Software 86, no. 11 (November 2013): 2822–40. http://dx.doi.org/10.1016/j.jss.2013.06.040.

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35

Amrita and Dilip Kumar Yadav. "A Novel Method for Allocating Software Test Cases." Procedia Computer Science 57 (2015): 131–38. http://dx.doi.org/10.1016/j.procs.2015.07.389.

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36

Pei, Songwen, Baifeng Wu, Kun Zhu, and Qiang Yu. "Novel software automated testing system based on J2EE." Tsinghua Science and Technology 12, S1 (July 2007): 51–56. http://dx.doi.org/10.1016/s1007-0214(07)70083-4.

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37

Akpabio, Usiereobong, Anthony N. Ede, Joshua Ivie, and Solomon Oyebisi. "Catalysing a Construction Project Using Novel Software Technology." IOP Conference Series: Materials Science and Engineering 640 (November 13, 2019): 012039. http://dx.doi.org/10.1088/1757-899x/640/1/012039.

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38

Stolarz, Maria, Maciej Żuk, Elżbieta Król, and Halina Dziubińska. "Circumnutation Tracker: novel software for investigation of circumnutation." Plant Methods 10, no. 1 (2014): 24. http://dx.doi.org/10.1186/1746-4811-10-24.

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39

Li, Yufeng, and Yankang Du. "A Novel Software-Defined Convolutional Neural Networks Accelerator." IEEE Access 7 (2019): 177922–31. http://dx.doi.org/10.1109/access.2019.2956841.

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40

Turnbull, A. M. J., M. S. Abu-Ain, S. C. Lash, A. S. Murphy, and A. J. Lotery. "Novel software to self-monitor central serous retinopathy." Eye 24, no. 1 (February 27, 2009): 179. http://dx.doi.org/10.1038/eye.2009.40.

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41

Guleria, Disha, and Aman Kaushik. "A Novel Evolutionary Approach to Software Cost Estimation." International Journal of Computer Applications 126, no. 4 (September 17, 2015): 47–52. http://dx.doi.org/10.5120/ijca2015906045.

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42

Singh, Gurvinder, and Jahid Ali. "A Novel Composite Approach for Software Clone Detection." International Journal of Computer Applications 126, no. 7 (September 17, 2015): 31–35. http://dx.doi.org/10.5120/ijca2015906098.

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43

Bubevski, Vojo. "A novel approach to software quality risk management." Software Testing, Verification and Reliability 24, no. 2 (January 10, 2013): 124–54. http://dx.doi.org/10.1002/stvr.1488.

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44

Dinneen, Jesse David, Ilja Frissen, Fabian Odoni, and Charles-Antoine Julien. "Cardinal: Novel software for studying file management behavior." Proceedings of the Association for Information Science and Technology 53, no. 1 (2016): 1–10. http://dx.doi.org/10.1002/pra2.2016.14505301062.

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45

Zhou, Lei, Guikai Peng, and Naresh Chand. "Demonstration of a novel software-defined Flex PON." Photonic Network Communications 29, no. 3 (March 26, 2015): 282–90. http://dx.doi.org/10.1007/s11107-015-0496-0.

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46

Mosley, M., and I. I. Vranic. "Earlier Diagnosis of ARVD/C With Novel Software." MD Conference Express 15, no. 22 (August 1, 2015): 13. http://dx.doi.org/10.1177/1559897715598152.

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47

Huang, H. C., and J. L. Wu. "Novel real-time software-based video coding algorithms." IEEE Transactions on Consumer Electronics 39, no. 3 (1993): 570–80. http://dx.doi.org/10.1109/30.234637.

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48

Nautiyal, Lata, Neena Gupta, and Sushil Chandra Dimri. "A Novel Approach to Component-Based Software Testing." ACM SIGSOFT Software Engineering Notes 39, no. 6 (December 9, 2014): 1–4. http://dx.doi.org/10.1145/2674632.2674640.

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49

Kumar Yogi, Manas, and Godavarthy Kavya. "Novel Emprical Methods for Advance Software Engineering Research." International Journal of Computer Science and Engineering 5, no. 7 (July 25, 2018): 14–20. http://dx.doi.org/10.14445/23488387/ijcse-v5i7p103.

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50

Zhu, Jing, Nan Zhou, Youjing Jiang, Li Wang, Wang He, Duo Peng, Qin Su, et al. "FLfinder: A novel software for the microhaplotype marker." Forensic Science International: Genetics Supplement Series 5 (December 2015): e622-e624. http://dx.doi.org/10.1016/j.fsigss.2015.10.002.

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