Command Line Interface

This paper examines computing academics' conceptions of the Unix operating system, and the purpose of teaching Unix. Interview transcripts from nine academics were analysed phenomenographically. A small number of qualitatively different conceptions of Unix were identified, within two broad categories. The first broad category manifested a technical approach to Unix. Within this broad category, the conceptions of Unix were, from the least to most sophisticated−(1) Unix as a set of unrelated commands;(2) Unix as a command line ...

White matter tractography enables studies of fiber bundle characteristics. Stochastic tractography facilitates these investigations by providing a measure of confidence regarding the inferred fiber bundles. This article presents a multithreaded ITK stochastic tractography filter that will enable novel studies of fiber tract abnormalities. Additionally, we provide an easy to use command line interface for the filter that is compatible with the 3D Slicer visualization environment.

Many human-computer interfaces are designed with the assumption that the user must adapt to the system, that users must be trained and their behavior altered to fit a given interface. The research presented here proceeds from the alternative assumption: Novice behavior is inherently sensible, and the computer system can be made to adapt to it. Specifically, a measurably easy-to-use interface was built to accommodate the actual behavior of novice users. Novices attempted an electronic mail task using a command-line interface containing no help, no menus, no documentation, and no instruction. A hidden operator intercepted commands when necessary, creating the illusion of an interactive session. The software was repeatedly revised to recognize users' new commands; in essence, the interface was derived from user behavior. This procedure was used on 67 subjects. The first version of the software could recognize only 7 percent of all the subjects' spontaneously generated commands;...

In recent years the power of Grid computing has grown exponentially through the development of advanced middleware systems. While usage has increased, the penetration of Grid computing in the scientific community has been less than expected by some. This is due to a steep learning curve and high entry barrier that limit the use of Grid computing and advanced cyberinfrastructure. In order for the scientists to focus on actual scientific tasks, specialized tools and services need to be developed to ease the integration of complex middleware. Our solution is Cyberaide Shell, an advanced but simple to use system shell which provides access to the powerful cyberinfrastructure available today. Cyberaide Shell provides a dynamic interface that allows access to complex cyberinfrastructure in an easy and intuitive fashion on an ad-hoc basis. This is accomplished by abstracting the complexities of resource, task, and application management through a scriptable command line interface. Through a service integration mechanism, the shell's functionality is exposed to a wide variety of frameworks and programming languages. Cyberaide Shell includes specialized experiment management and workflow commands that, with the scriptable nature of a shell, provide a set of services which where previously unavailable. The usability of Cyberaide Shell is demonstrated using a Water Threat Management application deployed on the TeraGrid.

Workflow management is an important part of scientific experiments. A common pattern that scientists are using is based on repetitive job execution on a variety of different systems, and managing such job execution is necessary for large-scale scientific workflows. The workflow system should also be client-based and able to handle multiple security contexts to allow researchers to take advantage of a diverse array of systems. We have developed, based on the Java Commodity Grid Kit (CoG Kit), a sophisticated and extensible workflow system that seamlessly integrates with the queueing system Cobalt through the advanced features provided by the CoG Kit.

Makalah ini membahas langkah-langkah rinci dalam proses instalasi Windows 10 menggunakan VirtualBox, serta pemanfaatan perintah dasar berbasis teks (Command Line Interface/CLI) di lingkungan Windows. Proses instalasi mencakup persiapan perangkat lunak, konfigurasi mesin virtual, instalasi sistem operasi, dan verifikasi akhir. Selain itu, penelitian ini mengulas perbedaan antara CLI dan GUI, perkembangan sistem operasi Microsoft Windows, serta manfaat dan penggunaan mesin virtual dalam berbagai konteks. Dengan mengikuti panduan yang disajikan, pengguna diharapkan mampu menginstal Windows 10 pada mesin virtual dengan tepat dan efisien, serta memanfaatkan perintah dasar CLI untuk berbagai tugas komputasi. Pemahaman ini tidak hanya meningkatkan keterampilan teknis pengguna tetapi juga memberikan wawasan yang lebih mendalam tentang cara kerja sistem operasi dan bagaimana teknologi virtualisasi dapat digunakan secara efektif. Manfaat yang diperoleh dari penggunaan mesin virtual dan CLI mencakup efisiensi sumber daya, fleksibilitas, keamanan, serta kemampuan untuk melakukan pengembangan dan pengujian perangkat lunak dalam lingkungan yang terkendali dan terisolasi. Makalah ini menyarankan peningkatan pemahaman teknologi virtualisasi, praktik rutin dengan CLI, eksplorasi sistem operasi lain, perhatian terhadap keamanan dan pemeliharaan mesin virtual, penerapan dalam proyek nyata, pelatihan dan kursus lanjutan, serta berbagi pengetahuan untuk pengembangan keterampilan teknis yang lebih lanjut dan optimalisasi penggunaan teknologi virtualisasi dan CLI.

The CMS experiment has to move Petabytes of data among dozens of computing centres with low latency in order to make efficient use of its resources. Transfer operations are well established to achieve the desired level of throughput, but operators lack a system to identify early on transfers that will need manual intervention to reach completion. File transfer latencies are sensitive to the underlying problems in the transfer infrastructure, and their measurement can be used as prompt trigger for preventive actions. For this reason, PhEDEx, the CMS transfer management system, has recently implemented a monitoring system to measure the transfer latencies at the level of individual files. For the first time now, the system can predict the completion time for the transfer of a data set. The operators can detect abnormal patterns in transfer latencies early, and correct the issues while the transfer is still in progress. Statistics are aggregated for blocks of files, recording a historical log to monitor the long-term evolution of transfer latencies, which are used as cumulative metrics to evaluate the performance of the transfer infrastructure, and to plan the global data placement strategy. In this contribution, we present the typical patterns of transfer latencies that may be identified with the latency monitor, and we show how we are able to detect the sources of latency arising from the underlying infrastructure (such as stuck files) which need operator intervention.

Keamanan sebuah aplikasi merupakan permasalahan terpenting dalam sebuah proses integrasi sistem informasi. Proses authentication dan authorization biasanya dilakukan menggunakan Single Sign On (SSO). Metode authentication dan authorization digunakan untuk mengamankan data dalam sebuah sistem. Proses authentication dan authorization dilakukan pada sisi client (web browser) berupa session dan sisi server (web server) berupa cookie. Session dan cookie merupakan harta yang berharga dalam proses authentication dan authorization karena berisi data yang diperlukan dalam proses login sehingga session dan cookie perlu diamankan. Session merupakan data kombinasi dari username dan password yang telah dilakukan proses enkripsi sedangkan cookie menyimpan data informasi login agar tetap dalam keadaan memperoleh akses sesuai dengan privilege yang telah diberikan kepada user. Begitu pentingnya peranan session dan cookie dalam proses authentication dan authorization sehingga diperlukan sebuah cara untuk mengamankan data pada session dan cookie. Salah satu cara mengamankan data adalah menggunakan REst API dan Auth Token.

Early undergraduate Grid computing courses generally took a bottom-up approach to Grid computing education starting with network protocols, client-server concepts, creating Web and Grid services, and then progressing through the underlying Grid computing middleware, security mechanisms and job submission all using a Linux command-line interface. We describe a new approach to teaching Grid computing beginning with a production-style Grid portal, registration process, and job submission, and then leading into infrastructure details. We incorporate seven assignments, several of which require students to install Grid computing software on their own computer or lab computers rather than using centralized servers. Students complete a "capstone" mini-project. Typical projects included creating a JSR 168 portlet user interface for an application. We describe our experiences using this new course structure.

Many human-computer interfaces are designed with the assumption that the user must adapt to the system, that users must be trained and their behavior altered to fit a given interface. The research presented here proceeds from the alternative assumption: Novice behavior is inherently sensible, and the computer system can be made to adapt to it. Specifically, a measurably easy-to-use interface was built to accommodate the actual behavior of novice users. Novices attempted an electronic mail task using a command-line interface containing no help, no menus, no documentation, and no instruction. A hidden operator intercepted commands when necessary, creating the illusion of an interactive session. The software was repeatedly revised to recognize users' new commands; in essence, the interface was derived from user behavior. This procedure was used on 67 subjects. The first version of the software could recognize only 7 percent of all the subjects' spontaneously generated commands;...

Previous work has found that recent computer science graduates often experience difficulty transitioning into their new roles in industry due to a significant gap between their academic experiences and industry's expectations. Although multiple studies have identified the views of students and members of industry on the value of a CS degree as preparation for industry, the faculty perspective on this topic remains unclear. Understanding these views could shed light on why the academia-industry gap has persisted despite the attention. This study identified faculty views on the goals of an undergraduate education and a CS major, focusing on preparation for careers in industry. In order to identify a spectrum of faculty views, we interviewed 14 faculty from a variety of backgrounds across three institutions. A phenomenographic analysis of the transcripts reveals that many faculty believe that industry preparation is an important programmatic goal, yet they encounter significant resource obstacles to achieving that goal.

Programming by demonstration enables users to easily personalize their applications, automating repetitive tasks simply by executing a few examples. We formalize programming by demonstration as a machine learning problem: given the changes in the application state that result from the user's demonstrated actions, learn the general program that maps from one application state to the next. We present a methodology

Technological systems and infrastructures form the bedrock of modern society and it is system administrators (sysadmins) who configure, maintain and operate these infrastructures. More often than not, they do so behind the scenes. The work of system administration tends to be unseen and, consequently, not well known. After all, do you think of your IT help-desk when everything is working just fine? Usually, people reach out for help when something is not working as expected or when they need something. A lot of work and effort goes into ensuring that systems are working as expected most of the time and, paradoxically, this smooth functioning results in the invisibilization of the work and effort that went into it.
This PhD research focuses on system administration work and what that entails in day-to-day tasks. Instead of proposing technical and social solutions, we try to better understand the “problem” that these proposed solutions are meant to solve. Drawing from safety science research and feminist research approaches, we perform a qualitative exploration of sysadmins’ work. We center their experiences via an in-depth interview investigation and a focus group study. We identify and describe the coordination mechanisms and gender considerations embedded in their work. We shed light on care work as part of sysadmin work and the phenomenon of double invisibility that is experienced by sysadmins who are not cis men. The thesis wraps up with a set of recommendations for moving toward safe and equitable work environments for sysadmins.

Programming by demonstration enables users to easily personalize their applications, automating repetitive tasks simply by executing a few examples. We formalize programming by demonstration as a machine learning problem: given the changes in the application state that result from the user's demonstrated actions, learn the general program that maps from one application state to the next. We present a methodology

Emerging technologies in the experimental sciences have opened the way for largescale experiments. Such experiments generate ever growing amounts of data from which researchers need to extract relevant pieces for subsequent analysis. R offers a great environment for statistical analysis. However, due to the diversity of possible data sources and formats, data preprocessing and import can be time consuming especially with data that require user interaction such as editing, filtering or formatting. Writing a code for these tasks can be time-consuming, error prone and rather complex. We present speedR, an Rpackage for interactive data import, filtering and code generation in order to address these needs. Using speedR, researchers can import new data, make basic corrections, examine current R session objects, open them in the speedR environment for filtering (subsetting), put the filtered data back into R, and even create new R functions with applied import and filtering constraints to speed up their productivity.

In this position paper, we examine factors, such as trust and usability, which can affect the adoption of an autonomic system. We argue that a system that exhibits initiative and strong communication skills is more likely to be adopted, and propose to treat humans as modeled, managed elements in an autonomic control loop to achieve these goals. We then propose some synergistic design ideas to make communicating with users more effective, and to allow the system to learn from the users' actions.

Emerging technologies in the experimental sciences have opened the way for largescale experiments. Such experiments generate ever growing amounts of data from which researchers need to extract relevant pieces for subsequent analysis. R offers a great environment for statistical analysis. However, due to the diversity of possible data sources and formats, data preprocessing and import can be time consuming especially with data that require user interaction such as editing, filtering or formatting. Writing a code for these tasks can be time-consuming, error prone and rather complex. We present speedR, an Rpackage for interactive data import, filtering and code generation in order to address these needs. Using speedR, researchers can import new data, make basic corrections, examine current R session objects, open them in the speedR environment for filtering (subsetting), put the filtered data back into R, and even create new R functions with applied import and filtering constraints to speed up their productivity.

The ongoing global COVID-19 pandemic made working from home -- wherever working remotely is possible -- the norm for what had previously been office-based jobs across the world. This change in how we work created a challenging situation for system administrators (sysadmins), as they are the ones building and maintaining the digital infrastructure our world relies on.

In this paper, we examine how system administration work changed early in the pandemic from sysadmins' personal perspectives, through semi-structured interviews and thematic analysis. We find that sysadmins faced a two-sided crisis: While sysadmins' own work environment changed, they also had to react to the new situation and facilitate stable options to work online for themselves and their colleagues, supporting their users in adapting to the crisis. This finding embeds into earlier work on the connection between IT (security) work and the notion of 'care', where we substantiate these earlier findings with results from a repeatable method grounded in coordination theory.

Furthermore, while we find that sysadmins perceived no major changes in the way they work, by consecutively probing our interviewees, we find that they did experience several counter-intuitive effects on their work. This includes that while day-to-day communication became inherently more difficult, other tasks were streamlined by the remote working format and were seen as having become easier. Finally, by structuring our results according to a model of coordination and communication, we identify changes in sysadmins' coordination patterns. From these we derive recommendations for how system administration work can be coordinated, ranging beyond the immediate pandemic response and the transition to any 'new normal' way of working.

Background Characterizing root system architecture (RSA) is essential to understanding the development and function of vascular plants. Identifying RSA-associated genes also represents an underexplored opportunity for crop improvement. Software tools are needed to accelerate the pace at which quantitative traits of RSA are estimated from images of root networks. Results We have developed GiA Roots (General Image Analysis of Roots), a semi-automated software tool designed specifically for the high-throughput analysis of root system images. GiA Roots includes user-assisted algorithms to distinguish root from background and a fully automated pipeline that extracts dozens of root system phenotypes. Quantitative information on each phenotype, along with intermediate steps for full reproducibility, is returned to the end-user for downstream analysis. GiA Roots has a GUI front end and a command-line interface for interweaving the software into large-scale workflows. GiA Roots can also be e...

Existing audio tools handle the increasing amount of computer audio data inadequately. The typical tape-recorder paradigm for audio interfaces is inflexible and time consuming, especially for large data sets. On the other hand, completely automatic audio analysis and annotation is impossible using current techniques. Alternative solutions are semi-automatic user interfaces that let users interact with sound in flexible ways based on content. This approach offers significant advantages over manual browsing, annotation and retrieval. Furthermore, it can be implemented using existing techniques for audio content analysis in restricted domains. This paper describes MARSYAS, a framework for experimenting, evaluating and integrating such techniques. As a test for the architecture, some recently proposed techniques have been implemented and tested. In addition, a new method for temporal segmentation based on audio texture is described. This method is combined with audio analysis techniques...

Proteins are post-translationally modified in vivo as part of cellular regulation and signaling, and undergo further chemical modifications during laboratory processing. Even relatively simple protein samples may carry a wide range of modifications. Peptide tandem mass spectrometry provides a way to study these events. We present a protocol for computational identification of posttranslational modifications (PTMs) and the sites where they occur. The protocol performs an unrestrictive search, and requires no prior knowledge of what modifications are present in the sample. We present a largely automated procedure for PTM discovery, and provide a guide for analysis of PTM annotations. This protocol requires you to type out several commands, so you may wish to enlist the help of a colleague familiar with the computer's command-line interface. A typical MS run of up to 25,000 scans can be searched and analyzed in 3 h. added in vivo, chemical changes induced during sample processing, and point mutations. This unrestrictive search is able to identify any modifications, including as-yet-unknown chemical events. The search is followed by a post-processing step. This step integrates information across many spectra (e.g., overlapping peptides) to confirm or discard modifications. The input to this protocol is a collection of tandem mass spectra that have been acquired from a mixture of peptides from proteolytically digested proteins. Our protocol presents the most common case of ion trap data digested with trypsin, and indicates points where you can specify a different instrument type and protease. The protocol has three major stages: (i) prepare the spectra and the protein database; (ii) search the spectra; and (iii) integrate the search results into a list of putative modifications. The output lists the peptide undergoing modification, the net mass (in Daltons) of the modification, and hypothetical chemical explanations for the modification. The protocol works on a computer running the Windows, Linux or Macintosh operating system. Some commands have slightly different syntax between operating systems; if so, both versions of the command are shown. Macintosh users should follow the instructions for Linux. The discussion of modified spectrum interpretation is applicable to the output of any unrestrictive search.

RESTful Web services have opened the door to clients to use Web sites in ways the original designers never imagined giving rise to the mashup phenomenon. The main advantage of the model based approach in Web engineering is that the models specify sort of contract the Web application adheres to and promises to deliver. Similarly, in RESTful scenario, mashup components responsible for delivering composite functionalities out of RESTful components could benefit from such contracts in search, automatic mashup, and other scenarios. Such scenarios ground the need for taking RESTful Web services in existing Web methods. This paper proposes the Application Facade Component Model in existing Web methods to support RESTful, resource-oriented architectures generation. Amazon Simple Storage Service is used as the running example and proof of concept to show advantages of such approach.

In this paper, we explore how anonymizing data to preserve privacy affects the utility of the classification rules discoverable in the data. In order for an analysis of anonymized data to provide useful results, the data should have as much of the information contained in the original data as possible. Therein lies a problem – how does one make sure that anonymized data still contains the information it had before anonymization? This question is not the same as asking if an accurate classifier can be built from the anonymized data. Often in the literature, the prediction accuracy of a classifier made from anonymized data is used as evidence that the data are similar to the original. We demonstrate that this is not the case, and we propose a new methodology for measuring the retention of the rules that existed in the original data. We then use our methodology to design three measures that can be easily implemented, each measuring aspects of the data that no pre-existing techniques ca...

The next generation of telemetry systems will rely heavily on XML-based standards. Multiple standards are currently being developed and reviewed by the T&E community, including iNET’s Metadata Description Language (MDL), the XML-version of IRIG 106, Chapter 9 (TMATS XML), the Instrumentation Hardware Abstraction Language (IHAL), and the Data Display Markup Language (DDML). In this paper, we share design considerations for developing XML-based T&E standards, gained from our experiences in designing IHAL and DDML.

Information and computing infrastructures (ICT) involve levels of complexity that are highly dynamic in nature. This is due in no small measure to the proliferation of technologies, such as: cloud computing and distributed systems architectures, data mining and multidimensional analysis, and large scale enterprise systems, to name a few. Effective computing and network systems administration is integral to the stability and scalability of these complex software, hardware and communication systems. Systems administration involves the design, analysis, and continuous improvement of the performance or operation of information and computing systems. Additionally, social and administrative responsibilities have become nearly as integral for the systems administrator as are the technical demands that have been imposed for decades. The areas of operations research (OR) and system dynamics (SD) modeling offer system administrators a rich array of analytical and optimization tools that have ...

Computer system administrators are the unsung heroes of the information age, working behind the scenes to configure, maintain, and troubleshoot the computer infrastructure that underlies much of modern life. However, little can be found in the literature about the practices and problems of these highly specialized computer users. We conducted a series of field studies in large corporate data centers, observing organizations, work practices, tools, and problem-solving strategies of system administrators. We found system administrators operate within large-scale, complex environments that present significant technical, social, cognitive, and business challenges. In this paper, we describe system administrator tool use in critical, high-cost, labor-intensive work through observational, survey, and interview data. We discuss our findings concerning administrator needs for coordinating work, maintaining situation awareness, planning and rehearsing complex procedures, building tools, and supporting complicated interleaved workflows.

Emerging technologies in the experimental sciences have opened the way for largescale experiments. Such experiments generate ever growing amounts of data from which researchers need to extract relevant pieces for subsequent analysis. R offers a great environment for statistical analysis. However, due to the diversity of possible data sources and formats, data preprocessing and import can be time consuming especially with data that require user interaction such as editing, filtering or formatting. Writing a code for these tasks can be time-consuming, error prone and rather complex. We present speedR, an Rpackage for interactive data import, filtering and code generation in order to address these needs. Using speedR, researchers can import new data, make basic corrections, examine current R session objects, open them in the speedR environment for filtering (subsetting), put the filtered data back into R, and even create new R functions with applied import and filtering constraints to speed up their productivity.

Programming by demonstration enables users to easily personalize their applications, automating repetitive tasks simply by executing a few examples. We formalize programming by demonstration as a machine learning problem: given the changes in the application state that result from the user's demonstrated actions, learn the general program that maps from one application state to the next. We present a methodology

RESTful Web services have opened the door to clients to use Web sites in ways the original designers never imagined giving rise to the mashup phenomenon. The main advantage of the model based approach in Web engineering is that the models specify sort of contract the Web application adheres to and promises to deliver. Similarly, in RESTful scenario, mashup components responsible for delivering composite functionalities out of RESTful components could benefit from such contracts in search, automatic mashup, and other scenarios. Such scenarios ground the need for taking RESTful Web services in existing Web methods. This paper proposes the Application Facade Component Model in existing Web methods to support RESTful, resource-oriented architectures generation. Amazon Simple Storage Service is used as the running example and proof of concept to show advantages of such approach.

Command-line interfaces are heavily used by system admin- istrators to manage computer systems. Tasks performed at a command line may often be repetitive, leading to a desire for automation. However, the critical nature of system adminis- tration suggests that humans also need to supervise an auto- mated system's behavior. This paper presents a programming by demonstration approach to capturing repetitive command- line procedures, which is based on a machine learning tech- nique called version space algebra. The interactive design of this learning system enables the user to supervise the system's training process, as well as allowing the user and system to alternate control of the learned procedure's execution.

Establishing users' identities before they access research infrastructure resources is a key feature of science gateways. With many science gateways now relying on general purpose gateway platform services, the challenges of managing identity-derived features have expanded to include authorization between science gateway tenants, middleware, and third party identity provider services. The latter include campus identity management systems. This paper examines the use of Keycloak as an implementation of an identity management system for Apache Airavata middleware, replacing our previous WSO2 Identity Server-based implementation. This effort raises larger issues that software-as-a-service communities should consider when embedding dependencies on third party software and services, including developing selection criteria and future-proofing systems.

One of the primary motivations behind autonomic computing (AC) is the problem of administrating highly complex systems. AC seeks to solve this problem through increased automation, relieving system administrators of many burdensome activities. However, the AC strategy of managing complexity through automation runs the risk of making management harder. We performed field studies of current administrator work practices to inform the design of AC in order to ensure that it simplifies system management. In this paper, we analyze what system administrators do in terms of three important activities: rehearsal and planning, maintaining situation awareness, and managing multitasking, interruptions and diversions. We provide guidelines for constructing AC environments that support these activities.

We have created open-source Simulink block libraries for ITK and VTK that allow pipelines for these toolkits to be built in a visual, drag-and-drop style within MATLAB. Each block contains an instance of an ITK or VTK class. Any block connections and parameters that the user makes within MATLAB’s Simulink visual environment are converted into connections and parameters for the ITK and VTK pipelines. In addition, we provide conversion of images to and from MATLAB arrays to allow MATLAB image processing blocks to be mixed with ITK and VTK blocks. The code for our block libraries is generated automatically from XML descriptions of the inputs, outputs, and parameters of the ITK and VTK classes. We have used these block libraries to build some example pipelines and believe that they will be useful for developing applications in image analysis and image-guided therapy.

White matter tractography enables studies of fiber bundle characteristics. Stochastic tractography facilitates these investigations by providing a measure of confidence regarding the inferred fiber bundles. This article presents a multithreaded ITK stochastic tractography filter that will enable novel studies of fiber tract abnormalities. Additionally, we provide an easy to use command line interface for the filter that is compatible with the 3D Slicer visualization environment.

This paper presents a tool for automatic generation of ANSI C code from models expressed in IOPT (Input-Output Place-Transition) Petri Nets. The inputs of the tool are PNML (Petri Nets Markup Language) files containing the IOPT Petri net models. The tool has two different interfaces: one relying on a simple graphical interface (amenable to be used by humans), and a second one with a command line interface (amenable to be used by humans as well as by other computational systems supporting tools interaction). The tool also allows the user to tune some parts of the automatically generated code considering some characteristics of the implementation platform improving the performance of the generated code. Generated code can be directly deployed into specific controllers; PIC low-cost microcontrollers as well as general purpose PCs have been used for validation.

White matter tractography enables studies of fiber bundle characteristics. Stochastic tractography facilitates these investigations by providing a measure of confidence regarding the inferred fiber bundles. This article presents a multithreaded ITK stochastic tractography filter that will enable novel studies of fiber tract abnormalities. Additionally, we provide an easy to use command line interface for the filter that is compatible with the 3D Slicer visualization environment.

Previous work has found that recent computer science graduates often experience difficulty transitioning into their new roles in industry due to a significant gap between their academic experiences and industry's expectations. Although multiple studies have identified the views of students and members of industry on the value of a CS degree as preparation for industry, the faculty perspective on this topic remains unclear. Understanding these views could shed light on why the academia-industry gap has persisted despite the attention. This study identified faculty views on the goals of an undergraduate education and a CS major, focusing on preparation for careers in industry. In order to identify a spectrum of faculty views, we interviewed 14 faculty from a variety of backgrounds across three institutions. A phenomenographic analysis of the transcripts reveals that many faculty believe that industry preparation is an important programmatic goal, yet they encounter significant resource obstacles to achieving that goal.

Interpretation of human genomes is a major challenge. We present the Scripps Genome ADVISER (SG-ADVISER) suite, which aims to fill the gap between data generation and genome interpretation by performing holistic, in-depth, annotations and functional predictions on all variant types and effects. The SG-ADVISER suite includes a de-identification tool, a variant annotation web-server, and a user interface for inheritance and annotation-based filtration. SG-ADVISER allows users with no bioinformatics expertise to manipulate large volumes of variant data with easewithout the need to download large reference databases, install software, or use a command line interface. SG-ADVISER is freely available at genomics.scripps.edu/ADVISER.

Knowledge about computer users is very beneficial for assisting them, predicting their future actions or detecting masqueraders. In this paper, an approach for creating and recognizing automatically the behavior profile of a user from the commands (s)he types in a commandline interface, is presented. Specifically, in this research, a computer user behavior is represented as a sequence of UNIX commands. This sequence is transformed into a distribution of relevant subsequences in order to find out a profile that defines its behavior. Then, statistical methods are used for recognizing a user from the commands (s)he types. The experiment results, using 2 different sources of UNIX command data, show that a system based on our approach can efficiently recognize a UNIX user. In addition, a comparison with a HMM-base method is done. Because a user profile usually changes constantly, we also propose a method to keep up to date the created profiles using an age-based mechanism.

Managing file systems of large organizations can present significant challenges in terms of the number of users, shared access to parts of the file system, and securing and monitoring critical parts of the file system. We present an interactive exploratory tool for monitoring and viewing the complex relationships within the Andrews File System (AFS). This tool is targeted as an aid to system administrators to manage users, applications and shared access. We tested our tool on UNC Charlotte's Andrews File System (AFS) file system, which contains 4554 users, 556 user groups, and 2.2 million directories. Two types of visualizations are supported to explore file system relationships. In addition, drill-down features are provided to access the user file system and access control information of any directory within the system. All of the views are linked to facilitate easy navigation.

For the past few years, a multidisciplinary team of computer and earth scientists at Lawrence Berkeley National Laboratory has been exploring the use of advanced user interfaces, commonly called {open_quotes}Virtual Reality{close_quotes} (VR), coupled with visualization and scientific computing software. Working closely with industry, these efforts have resulted in an environment in which VR technology is coupled with existing visualization and

Knowledge about computer users is very beneficial for assisting them, predicting their future actions or detecting masqueraders. In this paper, an approach for creating and recognizing automatically the behavior profile of a user from the commands (s)he types in a commandline interface, is presented. Specifically, in this research, a computer user behavior is represented as a sequence of UNIX commands. This sequence is transformed into a distribution of relevant subsequences in order to find out a profile that defines its behavior. Then, statistical methods are used for recognizing a user from the commands (s)he types. The experiment results, using 2 different sources of UNIX command data, show that a system based on our approach can efficiently recognize a UNIX user. In addition, a comparison with a HMM-base method is done. Because a user profile usually changes constantly, we also propose a method to keep up to date the created profiles using an age-based mechanism.

The Covid-19 that hit the world had an impact on the economy, especially in the trade sector, one of which was experienced by Small and Medium Enterprises (SMEs). Hanura Takeaway (Haway) is an SME engaged in the delivery of goods and food. To facilitate transactions for goods and food delivery services, it is necessary to develop applications that simplify the transaction process. In developing web services, it is necessary to exchange data that is accessed via standard internet protocols. Therefore, we need a web service in developing this application. Implementing a RESTful API web service will certainly facilitate the development of software applications outside the system or with different programming languages or platforms. This research will develop web service architecture using RESTful API in Takeaway application. To optimize the URI, several parameters are used, including filtering, sorting, selection and pagination. The Takeaway application consists of a website as a backend and an Android-based as a frontend. From the test results based on the function method using the Postman application, it shows that the REST API Sever built on the server has been running well. In testing the response time using the Apache JMeter application, the application shows a good response time. Meanwhile, the comparison of responses and requests to SOAP and REST architectures shows that REST takes faster time.

Students in the same statistics course learn different things, and view the role of the lecturer in different ways. We report on empirical research on students' conceptions of learning statistics, their expectations of teaching, and the relationship between them. The research ...

In this paper, we describe a research methodology phenomenography and its application in investigating the experience of an ensemble the recorder consort Fortune in negotiating a shared conception of pieces of music being prepared for recording and performance. This methodology been used previously by Reid to investigate music teachers' and students' conceptions of music and work as a musician. This resulted in the identification of a Music Entity, a tripartite hierarchy of understanding, moving from extrinsic technical, with its focus on technical proficiency and an orientation to correct, playing, through extrinsic meaning" finding the meaning in the music, to intrinsic meaning, focusing on the development and communication of personal meanings through music. Further research by Reid, Petoc: and co-researchers has shown the same tripartite conceptions of learning and working in a variety of other areas design, statistics, theology, environment resulting in the inter-disciplinary concept of the Professional Entity, Here, phenomenography is used to carry out an analysis of a small number of interviews with the members of an ensemble focusing on the process of moving from individual conceptions to a group conception of pieces of music, and then ensemble music as a whole. The analysis elucidates the process of negotiation between musicians in rehearsal and shows that the Professional Entity, is apparent in ensemble as well as solo music. The results of the study have important pedagogical implications, enabling teachers to help students develop their conceptions of music, while the methodology can be a useful tool for researchers in music education.

The paper focuses on security and performance concerns in mobile web development. The approach used in the study involved surveying journal publications to identify security and performance concerns. The paper highlights some of the contemporary issues currently being faced by application developers as they create, update and maintain mobile web applications including Cross-Site Scripting, Cookie hijacking/theft, location hijacking, history theft, behavior analysis, session hijacking, API design, security and the type of web server used considered.

Universities must compete in an increasingly difficult global market place. In order to successfully do so they must identify and profile market segments in order to achieve a unique selling position. Partnering may provide only part of the solution. The Cisco Network Academy Program (CNAP) is the world‘s largest network curriculum developed at an initial cost of US$75 million. There

Knowledge about computer users is very beneficial for assisting them, predicting their future actions or detecting masqueraders. In this paper, a new approach for creating and recognizing automatically the behaviour profile of a computer user is presented. In this case, a computer user behaviour is represented as the sequence of the commands (s)he types during her/his work. This sequence is transformed into a distribution of relevant subsequences of commands in order to find out a profile that defines its behaviour. Also, because of a user profile is not necessarily fixed but rather it evolves/changes, we propose an evolving method to keep up to date the created profiles using an Evolving Systems approach. In this paper we combine the evolving classifier with a trie-based user profiling to obtain a powerful self-learning on-line scheme. We also develop further the recursive formula of the potential of a data point to become a cluster centre using cosine distance which is provided in the Appendix. The novel approach proposed in this paper can be applicable to any problem of dynamic/evolving user behaviour modelling where it can be represented as a sequence of actions and events. It has been evaluated on several real data streams.