Статті в журналах з теми "Software assistant"

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1

Hayden, Charles C., John C. Mitchell, Jishnu Mukerji, and Frederick A. Schmidt. "The Software Development Assistant." AT&T Technical Journal 69, no. 2 (March 4, 1990): 76–90. http://dx.doi.org/10.1002/j.1538-7305.1990.tb00331.x.

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2

Benner, Kevin M. "Knowledge-based software assistant." Knowledge-Based Systems 1, no. 4 (September 1988): 221–26. http://dx.doi.org/10.1016/0950-7051(88)90032-9.

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3

Karimi, J., and B. R. Konsynsky. "An automated software design assistant." IEEE Transactions on Software Engineering 14, no. 2 (1988): 194–210. http://dx.doi.org/10.1109/32.4638.

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4

Hýža, Martin, Tomáš Skřont, and Petr Šilhán. "Drug interactions - experience with the software assistant." Psychiatrie pro praxi 21, no. 3 (December 10, 2020): 120–23. http://dx.doi.org/10.36290/psy.2020.021.

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5

Persons, Warren L. "The Safety-Critical Software Evaluation Assistant (SEA) *." IFAC Proceedings Volumes 28, no. 25 (November 1995): 95–100. http://dx.doi.org/10.1016/s1474-6670(17)44830-0.

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6

Halvoník, Dominik, and Peter Psenak. "Design of an Educational Virtual Assistant Software." International Journal of Emerging Technologies in Learning (iJET) 16, no. 11 (June 4, 2021): 308. http://dx.doi.org/10.3991/ijet.v16i11.19847.

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Despite the great creators’ efforts of e-learning educational materials, it is not possible to define the content of these materials specifically for all students. Based on this, it is necessary to provide in e-learning education the possibility of a more detailed interpretation of specific parts of the educational material that may be unclear to specific students. Based on this fact, we decided to take the first step in the form of software design, which will represent a virtual assistant in teaching computer science. The role of this assistant will be the ability to answer technical questions related to the presented curriculum. From an architectural point of view, it will be a set of micro-services, each of which will serve a specific task. The prerequisite is the use of decision trees to determine a specific micro-service, which will be implemented in the form of a neural network. Main aim of this paper is to provide detail description of global software architecture for such a virtual assistant
7

Nagargoje, Prof Vivek. "J.A.R.V.I.S Organizational Virtual Assistant." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (June 30, 2021): 4664–67. http://dx.doi.org/10.22214/ijraset.2021.35066.

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Chatbots, or conversational interfaces as they are also known, present a new way for individuals to interact with computer systems. Traditionally, to get a question answered by a software program involved using a search engine, or filling out a form. A chatbot allows a user to simply ask questions in the same manner that they would address a human. The most well known chatbots currently are voice chatbots: Alexa and Siri. However, chatbots are currently being adopted at a high rate on computer chat platforms. The technology at the core of the rise of the chatbot is natural language processing (“NLP”). A simple chatbot can be created by loading an FAQ (frequently asked questions) into chatbot software. The functionality of the chatbot can be improved by integrating it into the organization’s enterprise software, allowing more personal questions to be answered, like“When is the meet?”, or “What is the schedule of my day?”. A chatbot can be used as an “assistant” to a live agent, increasing the agent’s efficiency.
8

Bornemann, Lars, Volker Dicken, Jan-Martin Kuhnigk, Dag Wormanns, Hoen-Oh Shin, Hans-Christian Bauknecht, Volker Diehl, et al. "OncoTREAT: a software assistant for cancer therapy monitoring." International Journal of Computer Assisted Radiology and Surgery 1, no. 5 (December 15, 2006): 231–42. http://dx.doi.org/10.1007/s11548-006-0059-z.

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9

Bornemann, L., J. M. Kuhnigk, V. Dicken, S. Zidowitz, D. Wormanns, H. Shin, S. Krass, and H. O. Peitgen. "OncoTREAT—a software assistant for oncological therapy monitoring." International Congress Series 1281 (May 2005): 429–34. http://dx.doi.org/10.1016/j.ics.2005.03.050.

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10

Mertel, Adam, David Zbíral, Zdeněk Stachoň, and Hana Hořínková. "Historical geocoding assistant." SoftwareX 14 (June 2021): 100682. http://dx.doi.org/10.1016/j.softx.2021.100682.

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11

Alkodri, Ari Amir, Supardi Supardi, Burham Isnanto, and Kiswanto Kiswanto. "Selection of the Best Computer Laboratory Assistant Using AHP and Smart Methods." JURNAL SISFOTEK GLOBAL 12, no. 1 (March 29, 2022): 32. http://dx.doi.org/10.38101/sisfotek.v12i1.451.

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Computer Laboratory Assistant, abbreviated as ASLAB, includes a Lab Assistant in a Computer Laboratory. ASLAB helps improve service performance in the Computer Laboratory, such as assisting Lecturers when teaching practicum at the Computer Laboratory and assisting in installing software on Student laptops so that the performance of Computer Laboratory services is always good. Problems The Head of the Computer Laboratory has difficulty assessing the comparison of ASLAB with other ASLABs to determine the best or not good performance. The calculation of the final value uses the mean value method so that all criteria are considered to be of equal importance, so we cannot know which criterion is more important. The research objective is to apply the AHP and SMART methods for selecting the best Computer Laboratory Assistant so that it can determine the criteria and ranking weights for the best Computer Laboratory Assistant so that it can be used as a basis for decision making and applied by the Head of the Computer Laboratory in selecting the best Computer Laboratory Assistant.
12

Rosmiati, Rosmiati. "Sistem Pendukung Keputusan Pemilihan Asisten Laboratorium Menggunakan Metode Simple Additive Weighting (SAW)." Jurnal SAINTEKOM 6, no. 1 (March 3, 2017): 16. http://dx.doi.org/10.33020/saintekom.v6i1.3.

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Acceptance laboratory assistant in STMIK of Palangka Raya is one example of a case in making decision.Lecturers who became a selector of a practicum lecture will do selection acceptance assistant to the student who has registered as a candidate for assistant so that the process undertaken inaccurate in the selection process. the role of information technology is expected to be used to assist the lecturer in the process of acceptance of a laboratory assistant, so as to speed up the process and can produce the best decisions about anyone assistants who is received so that made the supporting system of decision selection laboratory assistant in STMIK of Palangka Raya which use method of Simple Additive Weighting (SAW). To make this system uses a method of SAW and the programming language used is Microsoft Visual Basic 6.0, then the system is developed using development method of software waterfall with design tools such as DFD (Data Flow Diagram) , ERD (Entity Relationship Diagram) and Database. With there is the Decision Support System that can be easier for STMIK of Palangka Raya in aiding the selection of a laboratory assistant so that can improve the quality of laboratory assistant.
13

Barrons, Robert. "Evaluation of personal digital assistant software for drug interactions." American Journal of Health-System Pharmacy 61, no. 4 (February 1, 2004): 380–85. http://dx.doi.org/10.1093/ajhp/61.4.380.

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14

Buckalew, Chris, and Alan Porter. "The lecturer's assistant." ACM SIGCSE Bulletin 26, no. 1 (March 12, 1994): 193–97. http://dx.doi.org/10.1145/191033.191105.

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15

Baranchuk, Vladislav A. "Virtual assistance information model for public services." Yugra State University Bulletin 15, no. 2 (December 10, 2019): 7–15. http://dx.doi.org/10.17816/byusu20190207-15.

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Currently, the world and Russia are rapidly developing the direction of developing virtual assistants. This is primarily due to the demands of business, the state and the population for this product, as well as the development of technologies capable of high-quality implementation of this product. Offers on virtual assistants for business and the public exist in large numbers: Google Assistant, Microsoft Cortana, Siri, etc. At the same time, there are no ready-made solutions for state needs in the market. The task of navigating public services today is the most relevant and relevant for the public sector. Solving this problem using a virtual assistant will save billions of rubles a year across the country. The article proposes an information model for the implementation of a virtual assistant for navigating public services. The basis of the intelligence of the developed virtual assistant is made up of artificial neural networks. The developed virtual assistant information model is implemented in the VIka software product. The trial operation of VIka takes place on the website of the administration of the Khanty-Mansiysk Autonomous Okrug Yugra, located at https://vi.admhmao.ru/chat/new.php. To date, VIka can help navigate services in 10 areas, such as healthcare, utilities, a line to kindergarten, etc.
16

Hyma, J., M. Rama Krishna Murty, and A. Naveen. "Personalized privacy assistant for digital voice assistants: Case study on Amazon Alexa." International Journal of Knowledge-based and Intelligent Engineering Systems 25, no. 3 (November 10, 2021): 291–97. http://dx.doi.org/10.3233/kes-210071.

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The advancements in modern technologies permit the invention of various digital devices which are controlled and activated by people’s gestures, touch and even by one’s voice. Google Assistant, iPhone Siri, Amazon Alexa etc., are most popular voice enabled devices which have grabbed the attention of digital gadget users. Their usage definitely makes the life easier and comfortable. The other side of these smart enabled devices is incredible violation of the privacy. This happens due to their continuous listening to the user and data transmission over a public network to the third-party services. The work proposed in this paper attempts to overcome the existing privacy violation problem with the voice enabled devices. The main idea is to incorporate an intelligent privacy assistant that works based on the user preferences over their data.
17

Al-Zaghameem, Abdullah O. "Evaluating the Role of Software Visualization Techniques as Assistant Tools in Software Reverse Engineering." International Journal of Software Engineering and Its Applications 12, no. 3 (October 31, 2018): 39–50. http://dx.doi.org/10.14257/ijseia.2018.12.3.04.

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18

Liu, Ge, and Hai Bing Zhang. "Voice Assistant — Application of Speech Recognition Technology in the Android System." Applied Mechanics and Materials 596 (July 2014): 384–87. http://dx.doi.org/10.4028/www.scientific.net/amm.596.384.

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This paper introduces the concept of Voice Assistant, the voice recognition service providers, several typical Voice Assistant product, and then the basic working process of the Voice Assistant is described in detail and proposed the technical bottleneck problems in the development of Voice Assistant software.
19

Tejaswi, Ch V. "Virtual Voice Assistant." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (June 30, 2021): 4097–101. http://dx.doi.org/10.22214/ijraset.2021.35868.

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This is desktop application which can assist people with basic tasks using natural language. Virtual Voice Assistants can go online and search for an answer to a user’s question. Actions can be triggered using text or voice. Voice is the key. A virtual voice assistant is a personal assistant which uses natural language processing (NLP) , voice recognition and speech synthesis to provide a service through a particular application. Natural Language Processing in short is called as NLP. It is basically a branch of artificial intelligence which mainly deals with the interaction between personal computers and human beings using the natural language. The main objective of NLP is to read, convert, understand, and make use of the human languages in a manner that is valuable. Voice recognition is a hardware device or computer software program with the potential to decode the voice of human beings. Voice recognition is usually used to operate a gadget, execute commands, or write without making use of any mouse, keyboard, or press any buttons. Artificial production of human speech is called as Speech Synthesis. A system used for this purpose is called a speech computer or speech synthesizer and can be implemented in many products of software’s and hardware’s.
20

Samuels, Leonard, and Janet N. Gordon. "Utility of a software assistant in critical care case review." American Journal of Emergency Medicine 15, no. 1 (January 1997): 43–48. http://dx.doi.org/10.1016/s0735-6757(97)90046-2.

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21

Huff, Karen E., and Victor R. Lesser. "A plan-based intelligent assistant that supports the software development." ACM SIGSOFT Software Engineering Notes 13, no. 5 (November 3, 1988): 97–106. http://dx.doi.org/10.1145/64137.65012.

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22

Huff, Karen E., and Victor R. Lesser. "A plan-based intelligent assistant that supports the software development." ACM SIGPLAN Notices 24, no. 2 (February 3, 1989): 97–106. http://dx.doi.org/10.1145/64140.65012.

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23

Yannibelli, Virginia, and Analía Amandi. "A knowledge-based evolutionary assistant to software development project scheduling." Expert Systems with Applications 38, no. 7 (July 2011): 8403–13. http://dx.doi.org/10.1016/j.eswa.2011.01.035.

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24

Yang, Cong Wei, Hai Tao Wu, and Hong Bin Liu. "Main Structure Design on Dual-Purpose Move-Assistant Device of Wheelchair and Crutch on SolidWorks." Advanced Materials Research 482-484 (February 2012): 2148–52. http://dx.doi.org/10.4028/www.scientific.net/amr.482-484.2148.

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Established the model of dual-purpose move-assistant device of wheelchair and crutch, using 3D modeling software SolidWorks, finished the 3D model of parts and parts assembly according to the design requirements of dual-purpose move-assistant device of wheelchair and crutch. Verified the accuracy of designing the project. With the software to carry on a 3D model design can save work time and economize the design budget, providing the theoretical feasibility of realizing the dual-purpose move-assistant device of wheelchair and crutch.
25

Overton, Sarah, and Yvonne Wren. "Outcome measurement using naturalistic language samples: A feasibility pilot study using language transcription software and speech and language therapy assistants." Child Language Teaching and Therapy 30, no. 2 (February 14, 2014): 221–29. http://dx.doi.org/10.1177/0265659013519251.

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The ultimate aim of intervention for children with language impairment is an improvement in their functional language skills. Baseline and outcome measurement of this is often problematic however and practitioners commonly resort to using formal assessments that may not adequately reflect the child’s competence. Language sampling, transcription and analysis provide a more thorough and realistic picture of a child’s abilities but are time consuming and usually considered unfeasible in the typical clinic setting. This article reports on a pilot study in which a speech and language therapy assistant (SLTA) carried out language transcription using language analysis software. Following a brief initial training period, the SLTA carried out transcriptions on 17 language samples at two time periods. Reliability between a speech and language therapist and the assistant’s transcriptions were calculated and were found to be acceptable for the majority of measures taken. The use of software by assistants is proposed as a viable alternative for outcome measurement of naturalistic language skills.
26

Scott, Melissa, Debra Hrelic, C. Elise Thompson, Yeoun Kim-Godwin, and Omar Alzaghari. "Establishing guidelines for teaching assistants in an online accelerated RN-BSN program." Journal of Educational Research and Reviews 9, no. 11 (November 17, 2021): 297–302. http://dx.doi.org/10.33495/jerr_v9i11.21.153.

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Effectively using teaching assistants is one strategy that can enhance engagement in a Community of Inquiry. This pilot study aimed to determine: 1) if standardized guidelines for teaching assistants improved student perceptions of the Community of Inquiry and 2) faculty satisfaction and intent to use the guidelines after study completion. A two-phase approach using the Community of Inquiry survey and open-ended questions assessed student perceptions of online learning and teaching assistant performance. Phase 1 data were used to develop teaching assistant guidelines. The guidelines were implemented in phase 2, and the survey was repeated. Faculty perceptions of the guidelines were ascertained through a separate survey. Descriptive and bivariate statistics measured quantitative data. Narrative analysis and NVivo software explored open-ended items.Students surveyed in Phase 1 reported positive perceptions of the Community of Inquiry on a 5-point Likert Scale (with 1 indicating strongly agree ad 2 indicating agree). Phase 2 revealed that students maintained positive perceptions of the Community of Inquiry, however, they were less positive than Phase 1. T-tests indicated no improvement in student perceptions after guideline implementation. Student concerns regarding the teaching assistant's performance were consistent in both phases. The faculty found guidelines helpful and intended to use them in the future. Student perceptions of Community of Inquiry in courses utilizing guidelines wereless positive than students taking classes without guidelines. Multifactorial issues, mainly COVID-19, impacted survey participation, engagement, andimplementation of guidelines. Despite this, findings led faculty to determine best practices for teaching assistants in accelerated online courses. Keywords: Teaching assistants, online learning, community of inquiry, guidelines.
27

Shetty, Siddharth, Mehul Padyal, Gauresh Tikam, and Ashwini Patil. "Fitverse: A Fitness Assistant Application using Flutter." International Journal for Research in Applied Science and Engineering Technology 10, no. 4 (April 30, 2022): 1152–55. http://dx.doi.org/10.22214/ijraset.2022.41470.

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Abstract: With reference to this document, it describes the process and components of the development of the project. A fitness schedule is any behavioral pattern that one often and regularly does, by and large automatically; and Fitverse- the fitness assistant application, is a tool that aids the user in their fitness journey by providing them with customized diet recommendations and workout schedules. It also monitors if and when you complete your desired diet and fitness targets and acts as a guide in one’s journey to achieve the aspired fitness goals. Turning good behaviors into habits makes them our default, automatic choices of action. This all but eliminates the willful effort required to repeat them. It aids users with their fitness journey by being the virtual fitness trainer. Fitverse is an android-based application built using Flutter that helps in achieving fitness goals and building concrete habits. The Prototype Model is used to develop this system along with iterative software development model. As for the software used to develop this system is Visual studio code and programming language used is Dart with Firebase as the database. This technology can transform the current daunting task to develop a fitness schedule or a habit and make it more efficient and easier. Keywords: Dart language, Flutter, Iterative Software Development Model, Prototype Model, Firebase
28

Shade, Marcia, Kyle Rector, Rasila Soumana, and Kevin Kupzyk. "You Have One Reminder: Self-Manage Your Pain." Innovation in Aging 4, Supplement_1 (December 1, 2020): 205. http://dx.doi.org/10.1093/geroni/igaa057.664.

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Abstract Pain has a significant impact in the lives of aging adults. As the population of America grows older, they need to be encouraged to use pain self-management strategies. Technology is an option, but current pain management applications have usability limitations in older adults. This feasibility study describes the usability of voice assistant reminders for pain self-management. We enrolled 15 community-dwelling aging adults with chronic pain. Participants created two pre-determined voice assistant reminder tasks: 1) to take scheduled pain medication, and 2) to write in a pain diary. We collected data on demographics, pain, confidence of managing symptoms, and objective ease of use. After four weeks, we collected information about subjective ease of use and usefulness of the voice assistant. Participants were mostly female, average age 65 years; reporting moderate pain severity 4.58 (SD 2.29) and pain interference 3.94 (SD 2.62). The mean PROMIS self-efficacy for managing symptoms score was 50.8 (SD 8.2). Voice assistant usability was above average (78 out of 100). The median time to make a voice assistant profile was five minutes (SD 7.5), with a median of seeking help two times. No significant relationships were found between pain and usability. Three participants made physical activity and distraction reminders to self-manage pain. Voice assistant reminders were perceived as consistent, easy to set up and helpful for accountability. Older users may provide helpful feedback for development and testing of voice assistant software for pain self-management. Voice assistants may provide helpful reminders that encourage the completion of pain self-management strategies.
29

Ciarallo, Frank W., Vinu V. Panicker, Sriram Mahadevan, and Raymond R. Hill. "A Hybrid Intelligent Logistics Diagnostic Assistant." Journal of Decision Systems 14, no. 3 (January 2005): 215–40. http://dx.doi.org/10.3166/jds.14.215-240.

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30

Kumar, Dr Ranjeet, Muhammad Faisal, Mohd Faisal, and Owaish Ahmad. "My Voice Assistant Using Python." International Journal for Research in Applied Science and Engineering Technology 10, no. 4 (April 30, 2022): 3004–7. http://dx.doi.org/10.22214/ijraset.2022.41958.

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Abstract: In the current situation of technology development within the field of augmented reading and voice assistant systems development, many researchers are writing in this regard for the development of new and effective technologies. The voice assistant are software package agents that may interpret human speech & responds via synthesized voices apple siri, microsoft cortana & google assistant are the foremost common voice assistant & embedded in smartphones .Today the technological advancement is increasing day by day. with the assistance of computer system in which we are able to do solely few task however currently artificial intelligence ,machine learning and few a lot of technologies have created computer system so advance that we are able to implement any type of task. In the present paper, The thought of speech technology extremely encompasses 2 technologies: Synthesizer and recognizer. A speech synthesizer takes as input and produces an audio stream as output. A speech recognizer on the opposite hand does opposite. It takes an audio stream as input and thus turns it into text transcription. The voice may be a signal of infinite information. for this reason, we have got created our own virtual personal assistant just for windows using python 3.6 that is ready to right to use on any windows explorer such as windows 7,8,10.we will use python as a programming language as a result of it have a major libraries which is use to implement command. Index Term: Artificial Intelligence, Desktop Assistant, Python, Text to Speech, Virtual Assistant, Voice Recognition.
31

Jevtic, Aleksandar, Andres Flores Valle, Guillem Alenya, Greg Chance, Praminda Caleb-Solly, Sanja Dogramadzi, and Carme Torras. "Personalized Robot Assistant for Support in Dressing." IEEE Transactions on Cognitive and Developmental Systems 11, no. 3 (September 2019): 363–74. http://dx.doi.org/10.1109/tcds.2018.2817283.

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32

MacGregor, D. L., S. Tallett, S. MacMillan, R. Gerber, and H. O'Brodovich. "Clinical and Education Workload Measurements Using Personal Digital Assistant-Based Software." PEDIATRICS 118, no. 4 (October 1, 2006): e985-e991. http://dx.doi.org/10.1542/peds.2006-0515.

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33

Crasso, Marco, Alejandro Zunino, Leonardo Moreno, and Marcelo Campo. "JEETuningExpert: A software assistant for improving Java Enterprise Edition application performance." Expert Systems with Applications 36, no. 9 (November 2009): 11718–29. http://dx.doi.org/10.1016/j.eswa.2009.04.024.

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34

Robinson, Robert L., and Martha S. Burk. "Identification of drug-drug interactions with personal digital assistant–based software." American Journal of Medicine 116, no. 5 (March 2004): 357–58. http://dx.doi.org/10.1016/j.amjmed.2003.09.025.

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35

CHLIPALA, ADAM. "Modular development of certified program verifiers with a proof assistant,." Journal of Functional Programming 18, no. 5-6 (August 15, 2008): 599–647. http://dx.doi.org/10.1017/s0956796808006904.

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AbstractWe report on an experience using the Coq proof assistant to develop a program verification tool with a machine-checked proof of full correctness. The verifier is able to prove memory safety of x86 machine code programs compiled from code that uses algebraic datatypes. The tool's soundness theorem is expressed in terms of the bit-level semantics of x86 programs, so its correctness depends on very few assumptions. We take advantage of Coq's support for programming with dependent types and modules in the structure of the development. The approach is based on developing a library of reusable functors for transforming a verifier at one level of abstraction into a verifier at a lower level. Using this library, it is possible to prototype a verifier based on a new type system with a minimal amount of work, while obtaining a very strong soundness theorem about the final product.
36

Park, Soo Jin, Eun Ji Lee, Se Ik Kim, Seong-Ho Kong, Chang Wook Jeong, and Hee Seung Kim. "Clinical Desire for an Artificial Intelligence–Based Surgical Assistant System: Electronic Survey–Based Study." JMIR Medical Informatics 8, no. 5 (May 15, 2020): e17647. http://dx.doi.org/10.2196/17647.

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Background Techniques utilizing artificial intelligence (AI) are rapidly growing in medical research and development, especially in the operating room. However, the application of AI in the operating room has been limited to small tasks or software, such as clinical decision systems. It still largely depends on human resources and technology involving the surgeons’ hands. Therefore, we conceptualized AI-based solo surgery (AISS) defined as laparoscopic surgery conducted by only one surgeon with support from an AI-based surgical assistant system, and we performed an electronic survey on the clinical desire for such a system. Objective This study aimed to evaluate the experiences of surgeons who have performed laparoscopic surgery, the limitations of conventional laparoscopic surgical systems, and the desire for an AI-based surgical assistant system for AISS. Methods We performed an online survey for gynecologists, urologists, and general surgeons from June to August 2017. The questionnaire consisted of six items about experience, two about limitations, and five about the clinical desire for an AI-based surgical assistant system for AISS. Results A total of 508 surgeons who have performed laparoscopic surgery responded to the survey. Most of the surgeons needed two or more assistants during laparoscopic surgery, and the rate was higher among gynecologists (251/278, 90.3%) than among general surgeons (123/173, 71.1%) and urologists (35/57, 61.4%). The majority of responders answered that the skillfulness of surgical assistants was “very important” or “important.” The most uncomfortable aspect of laparoscopic surgery was unskilled movement of the camera (431/508, 84.8%) and instruments (303/508, 59.6%). About 40% (199/508, 39.1%) of responders answered that the AI-based surgical assistant system could substitute 41%-60% of the current workforce, and 83.3% (423/508) showed willingness to buy the system. Furthermore, the most reasonable price was US $30,000-50,000. Conclusions Surgeons who perform laparoscopic surgery may feel discomfort with the conventional laparoscopic surgical system in terms of assistant skillfulness, and they may think that the skillfulness of surgical assistants is essential. They desire to alleviate present inconveniences with the conventional laparoscopic surgical system and to perform a safe and comfortable operation by using an AI-based surgical assistant system for AISS.
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Felkey, Bill G., and Brent I. Fox. "The Case for the Personal Digital Assistant (PDA)." Hospital Pharmacy 37, no. 4 (April 2002): 418–22. http://dx.doi.org/10.1177/001857870203700412.

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This continuing series will be a valuable resource for both experienced and novice users of handheld computer technology. Topics will include how to evaluate hardware and software, clinical and business applications, and the development of a “digital peripheral brain.” The authors will also discuss PDA organization skills that can maximize professional and personal efficiency.
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Colombo, Giorgio, Giancarlo Facoetti, Stella Gabbiadini, and Caterina Rizzi. "Socket modelling assistant for prosthesis design." International Journal of Computer Aided Engineering and Technology 5, no. 2/3 (2013): 216. http://dx.doi.org/10.1504/ijcaet.2013.052930.

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39

Wilde, Norman, and Stephen M. Thebaut. "The maintenance assistant: Work in progress." Journal of Systems and Software 9, no. 1 (January 1989): 3–17. http://dx.doi.org/10.1016/0164-1212(89)90003-4.

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LASCAULT, GILLES, RÉMI NITZSCHÉ, PHILIPPE RITTER, MARTINE REMY, and MARCEL LIMOUSIN. "Assistant Programming Software: A New Tool for an Improved Programming of Pacemakers." Pacing and Clinical Electrophysiology 13, no. 12 (December 1990): 1732–36. http://dx.doi.org/10.1111/j.1540-8159.1990.tb06881.x.

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41

Popov Zambiasi, Saulo, and Ricardo Jose Rabelo. "A Proposal for Reference Architecture for Personal Assistant Software Based on SOA." IEEE Latin America Transactions 10, no. 1 (January 2012): 1227–34. http://dx.doi.org/10.1109/tla.2012.6142466.

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42

Broy, Manfred. "Experiences with software specification and verification using LP, the Larch proof assistant." Formal Methods in System Design 8, no. 3 (May 1996): 221–72. http://dx.doi.org/10.1007/bf00709138.

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43

Bukhori, Iqbal, Imas Siti Rojab, Iwan Sopwandin, and Ara Hidayat. "Pendayagunaan Software Asisten Dalam Pengelolaan Sistem Informasi Manajemen Keuangan Sekolah." TADBIR MUWAHHID 4, no. 1 (April 1, 2020): 13. http://dx.doi.org/10.30997/jtm.v4i1.2481.

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This study aims to determine the management of the school's financial management system in Madrasah Aliyah Al-mu'awanah and the implementation of Assistant software utilization in the management of the school's financial management system in Al-Mu'awanah Madrasah. This research uses an approach to research and development (R & D) research. Research results show that in practice financial management in Madrasah Aliyah Al-mu'awanah is still based on a manual input data system so that in the process there are obstacles especially in data processing and school financial data recapitulation. Implementation of the use of assistant software in the process of school financial information management provides a positive picture, the statement is reinforced by the presence of a good response from respondents. Based on the distribution of the questionnaire that has been given to the respondents, the percentage of eligibility is 84%. The percentage of feasibility obtained shows that the utilization of computerized software or financial software is feasible to be used as school financial administration software, especially in Madrasah Aliyah Al-Mu'awanah.
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Kivugo, Ramadhani O., and Zhong Min Wang. "Study on Modeling and Kinematics Analysis of an Assistant Robot." Applied Mechanics and Materials 299 (February 2013): 48–51. http://dx.doi.org/10.4028/www.scientific.net/amm.299.48.

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Firstly, model of an assistant robot is built by UG software based on analysis to human exoskeleton system. Secondly, for establishing its kinematics model of this assistant robot, physical characteristics, practical geometric parameters and restriction relations are considered, and then this model is exported to ADAMS environment. Thirdly, simulation studies to the assistant robot system are carried out by ADAMS, and its kinematics performances are analyzed. Simulation experiments verify the validity and feasibility of the modeling and kinematics analysis method.
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Жолудев, С., S. Zholudev, В. Стрижаков, V. Strizhakov, А. Ремов, A. Remov, Д. Жолудев, D. Zholudev, П. Нерсесян, and P. Nersesyan. "Role of the dentist orthopedist in implant placement planning using surgical templates and software complex implant-assistant®." Actual problems in dentistry 11, no. 4 (October 25, 2015): 54–63. http://dx.doi.org/10.18481/2077-7566-2015-11-54-63.

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<p>In the article on the basis of the literature are shown main errors during dental implantation, as well as the difficulties encountered by the dentist orthopedist during the stage of prosthetics on implants<br />in the absence of parallel superstructures, as well as improperly installed cylindrical implants. On the example of the technology of the planning of surgical stage of implant placement using a surgical<br />template and software complex IMPLANT-ASSISTANT® is shown that orthopedist can not only plan the position of the implants, but also to predict the outcome of orthopedic treatment of partial or total loss of teeth with implants. The article shows the algorithms of treatment of patients with surgical guide and software complex IMPLANT-ASSISTANT®, as well as on clinical examples illustrates the results of this technology. It is talked about future work results of the medical team in Yekaterinburg.</p>
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Deshmukh, Prof Anushree, Smit Shah, Heena Puthran, and Naisargi Shah. "Virtual Shopping Assistant for Online Fashion Store." International Journal for Research in Applied Science and Engineering Technology 10, no. 5 (May 31, 2022): 110–17. http://dx.doi.org/10.22214/ijraset.2022.42099.

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Abstract: A new way for individuals to interact with computer systems will be done through chatbots or conversational interfaces. Historically, introducing a matter answered by a software package involves employing a program or filling out a type. The technology at the core of the increase of the chatbot is NLP i.e., Natural Language Processing. Sequence to Sequence (often abbreviated to seq2seq) fashions is a specific type of Recurrent Neural Network architectures that we commonly use (but no longer restricted) to clear up complicated Language issues like Machine Translation, Question Answering, growing Chatbots, Text Summarization, and so forth. Recent advances in machine learning have greatly improved the accuracy and effectiveness of NLP, creating chatbots a viable choice for several organizations like e-commerce, Customer service, Conversational apps, social media, Sales/Marketing/Branding, as Voice modules, Travel industry, Medicine, Hospitality, Human Resources etc. An NLP primarily based chatbot is a pc software or synthetic brain that communicates with a patron by means of textual or sound strategies This improvement in NLP is firing a great deal of additional analysis and research which should lead to continued growth in the effectiveness of chatbots in the years to come. Stochastic gradient descent (often abbreviated SGD) is an iterative approach for optimizing an goal characteristic with appropriate smoothness homes (e.g. differentiable or sub differentiable). Usage of Chatbots can also prove to be beneficial in ways like economically offering 24/7 service, improving customer satisfaction, reaching a younger demographic, reducing costs, increasing revenue and much more. Keywords: Chatbots, Natural Language Processing (NLP), Stochastic Gradient Descent (SGD), Sequential Model, Machine Learning
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Hvannberg, E. T., and M. S. Krishnamoorthy. "An object-based parallel programming assistant." ACM SIGPLAN Notices 24, no. 4 (April 1989): 200–202. http://dx.doi.org/10.1145/67387.67444.

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Mayer, Richard J., Chuan-Jun Su, and Arthur K. Keen. "An integrated manufacturing planning assistant ? IMPA." Journal of Intelligent Manufacturing 3, no. 2 (April 1992): 109–22. http://dx.doi.org/10.1007/bf01474750.

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49

Sadi, Mahsa H., and Eric Yu. "RAPID: a knowledge-based assistant for designing web APIs." Requirements Engineering 26, no. 2 (February 3, 2021): 185–236. http://dx.doi.org/10.1007/s00766-020-00342-0.

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50

Mitani, Atsushi, and Masumi Muramatsu. "Development of Human Tongue Model for Mealtime Assistant Training Using Oral Care Simulation Model." International Journal of Automation Technology 13, no. 4 (July 5, 2019): 499–505. http://dx.doi.org/10.20965/ijat.2019.p0499.

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In the recent years, Japan has been facing the problem of an aged society, and oral care is an important aspect in maintaining the oral health of elderly persons. Swallowing disorders, caused by various factors, are one of the most severe oral problems associated with advancing age. A mealtime assistant can help elderly persons in this situation, and thus, mealtime assistance is considered as an essential skill for students in nursing education. There are, however, some problems in mealtime assistant training in nursing schools. For example, there are few instructors compared to the number of students and few opportunities in clinical situations. Therefore, training through simulation has received significant attention as an effective educational process for students in medical and nursing schools. We have attempted to develop an oral care simulator and corresponding software to provide nursing students with an effective oral care training environment. Previously, we developed a prototype model of an oral care simulator for learning tooth brushing. In this study, we developed a tongue model for a mealtime assistant simulation model. Incorrect meal assistance may lead to mouth injury and aspiration pneumonia. To prevent such situations, the caregiver must serve the meal on an appropriate position on the tongue using a spoon, and must release it safely. This paper describes a summary of the developed mealtime assistant simulator and the procedures of tongue model development using three-dimensional computer-assisted design (3D-CAD) and 3D printing. We also developed a sensor system to be embeded in the tongue model to detect spoon motion. The sensor system for the tongue model was evaluated through spoon detection experiments.

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