Review of research in feature-based design

Research in feature-based design is reviewed. Feature-based design is regarded as a key factor towards CAD/CAPP integration from a process planning point of view. From a design point of view, feature-based design offers possibilities for supporting the design process better than current CAD systems do. The evolution of feature definitions is briefly discussed. Features and their role in the design process and as representatives of design-objects and design-object knowledge are discussed. The main research issues related to feature-based design are outlined. These are: feature representation, features and tolerances, feature validation, multiple viewpoints towards features, features and standardization, and features and languages. An overview of some academic feature-based design systems is provided. Future research issues in feature-based design are outlined. The conclusion is that feature-based design is still in its infancy, and that more research is needed for a better support of the design process and better integration with manufacturing, although major advances have already been made

The role of sex differences in detecting deception in computer-mediated communication in English

[EN] While deception seems to be a common approach in interpersonal communication, most examination on interpersonal deception sees the sex of the interlocutor as unconnected with the capability to notice deceptive messages. This research studies the truth and deception detection capability of both male and female receivers when replying to both true and deceptive messages from both male and female speakers. The outcomes indicate that sex may be a significant variable in comprehending the interpersonal detection probabilities of truth and of lies. An interaction of variables including the speakers’ sex, receivers’ sex, and whether the message appears to be truthful or deceptive is created to relate to detection capability.Kuzio, A. (2018). The role of sex differences in detecting deception in computer-mediated communication in English. Journal of Computer-Assisted Linguistic Research. 2(1):39-53. doi:10.4995/jclr.2018.10521SWORD395321Aamodt, M. G., & Custer, H. (2006). Who can best catch a liar? A meta-analysis of individual differences in detecting deception. The Forensic Examiner, 15(1), 6-11.Blalock, H. M. (1972). Social Statistics. New York: McGraw Hill.Bond, C. F., & DePaulo, B. M. (2006). Accuracy of deception judgments. Personality and Social Psychology Review, 10(3), 214-234. https://doi.org/10.1207/s15327957pspr1003_2Boush, D. M., Friestad, M., & Wright, P. (2009). Deception in the marketplace : The psychology of deceptive persuasion and consumer self-protection. New York: Routledge.Camden, C., Motley, M. T., & Wilson, A. (1984). White lies in interpersonal communication: A taxonomy and preliminary investigation of social motivations. Western Journal of Speech Communication, 48(4), 309-325. https://doi.org/10.1080/10570318409374167Carlson, J., George, J., Burgoon, J., Adkins, M., & White, C. (2004). Deception in computer mediated communication. Group Decision and Negotiation, 13, 5-28. https://doi.org/10.1023/B:GRUP.0000011942.31158.d8Daft, R.L. & Lengel, R.H. (1986). Information richness: A new approach to managerial behavior and organizational design. In Cummings, L. L. & Staw, B.M. (Eds.), Research in organizational behavior 6 (pp. 191-233). Homewood, IL: JAI Press.DePaulo, B. M., Epstein, J. A., & Wyer, M. M. (1993). Sex differences in lying: How women and men deal with the dilemma of deceit. In M. Lewis, & C. Saarni (Eds.), Lying and deception in everyday life (pp. 126-147). New York: Guilford Press.DePaulo, B. M., Kashy, D. A., Kirkendol, S. E., Wyer, M. M., & Epstein, J. A. (1996). Lying in everyday life. Journal of Personality and Social Psychology, 70(5), 979- 995. https://doi.org/10.1037/0022-3514.70.5.979DePaulo, B. M., Kirkendol, S. E., Tang, J., & O'Brien, T. P. (1988). The motivational impairment effect in the communication of deception: Replications and extensions. Journal of Nonverbal Behavior, 12(3), 177-202. https://doi.org/10.1007/BF00987487DePaulo, B. M., Lassiter, G. D., & Stone, J. L. (1982). Attention all determinants of success at detecting deception and truth. Personality and Social Psychology Bulletin, 8(2), 273-279. https://doi.org/10.1177/0146167282082014DePaulo, B. M., & Rosenthal, R. (1981). Telling lies. Journal of Personality and Social Psychology, 37(10), 1713-1722. https://doi.org/10.1037/0022-3514.37.10.1713Dreber, A., & Johannesson, M. (2008). Gender differences in deception. Economics Letters, 99(1), 197-199. https://doi.org/10.1016/j.econlet.2007.06.027Ekman, P., & O'Sullivan, M. (1991). Who can catch a liar? American Psychologist, 46(9), 913-920. https://doi.org/10.1037/0003-066X.46.9.913Ekman, P., O'Sullivan, M., & Frank, M. G. (1999). A few can catch a liar. Psychological Science, 10(3), 263-266. https://doi.org/10.1111/1467-9280.00147Feldman, R. S., Forrest, J. A., & Happ, B. R. (2002). Self-presentation and verbal deception: Do self-presenters lie more? Basic and Applied Social Psychology, 24(2), 163-170. https://doi.org/10.1207/153248302753674848George, J. F., & Robb, A. (2008). Deception and computer-mediated communication in daily life. Communication Reports, 21(2), 92-103. https://doi.org/10.1080/08934210802298108Hample, D. (1980). Purposes and effects of lying. Southern Speech Communication Journal, 46(1), 33-47. https://doi.org/10.1080/10417948009372474Hancock, J., Thom-Santelli, J., & Ritchie, T. (2004). Deception and design: The impact of communication technology on lying behavior. In E. Dykstra-Erickson, & M. Tscheligi (Eds.), Proceedings of the 2004 conference on human factors in computing systems (pp. 129-134). New York: Association for Computing Machinery.https://doi.org/10.1145/985692.985709Haselton, M. G., Buss, D. M., Oubaid, V., & Angleitner, A. (2005). Sex, lies, and strategic interference: The psychology of deception between the sexes. Personality and Social Psychology Bulletin, 31(1), 3-23. https://doi.org/10.1177/0146167204271303Inglehart, R., Basa-ez, M., & Moreno, A. (1998). Human values and beliefs: A crosscultural sourcebook. Ann Arbor, MI: University of Michigan Press. https://doi.org/10.3998/mpub.14858Knapp, L. M., Hart, R. P., & Dennis, H. S. (1974). An exploration of deception as a communication construct. Human Communication Research, 1(1), 15-29. https://doi.org/10.1111/j.1468-2958.1974.tb00250.xKraut, R. E. (1980). Behavioral roots of person perception: The deception judgments of customs inspectors and laymen. Journal of Personality and Social Psychology, 39(5), 784-798. https://doi.org/10.1037/0022-3514.39.5.784Kuzio, A. (2018). Cross-cultural Deception in Polish and American English in Computer-Mediated Communication. New Castle upon Tyne: Cambridge Scholars Publishing.Levine, T. R., & Kim, R. K. (2010). Some considerations for a new theory of deceptive communication. In M. S. McGlone, & M. L. Knapp (Eds.), The interplay of truth and deception: New agendas in theory and research (pp. 16-34). New York: Routledge.Levine, T. R., Park, H. S., & McCornack, S. A. (2006). Accuracy in detecting truths and lies: Documenting the "Veracity Effect". Communication Monographs, 66(2), 125- 144. https://doi.org/10.1080/03637759909376468Manstead, A., Wagner, H. L., & McDonald, C. J. (1986). Deceptive and non-deceptive communications: Sending experience, modality, and individual abilities. Journal of Nonverbal Behavior, 10(3), 147-167. https://doi.org/10.1007/BF00987612McCornack, S. A., & Parks, M. R. (1990). What women know that men don't: Sex differences in determining the truth behind deceptive messages. Journal of Social and Personal Relationships, 7(1), 107-118. https://doi.org/10.1177/0265407590071006Park, H. S., Levine, T. R., McCornack, S. A., Morrison, K., & Ferrara, M. (2002). How people really detect lies. Communication Monographs, 69(2), 144-157. https://doi.org/10.1080/714041710Prater, T., & Kiser, S. B. (2002). Lies, lies, and more lies. SAM Advanced Management Journal,67(2), 9-36.Sanchez-Pages, S., & Vorsatz, M. (2008). Enjoy the silence: An experiment on truthtelling. Experimental Economics, 12(2), 220-241. https://doi.org/10.1007/s10683-008-9211-7Seiter, J. S., Bruschke, J., & Bai, C. (2002). The acceptability of deception as a function of perceivers' culture, deceiver's intention, and deceiver-deceived relationship. Western Journal of Communication, 66(2), 158-180. https://doi.org/10.1080/10570310209374731Serota, K. B., Levine, T. R., & Boster, F. J. (2010). The prevalence of lying in America: Three studies of self-reported lies. Human Communication Research, 36(1), 2-25. https://doi.org/10.1111/j.1468-2958.2009.01366.xTurner, R. E., Edgley, C., & Olmstead, G. (1975). Information control in conversations: Honesty is not always the best policy. Kansas Journal of Sociology, 11(1), 69-89.https://doi.org/10.17161/STR.1808.6098Zuckerman, M., DePaulo, B. M., & Rosenthal, R. (1981). Verbal and nonverbal communication of deception. In L. Berkowitz (Ed.), Advances in experimental social psychology (volume 11, pp. 1-59). New York: Academic Press.https://doi.org/10.1016/S0065-2601(08)60369-

Abstract State Machines 1988-1998: Commented ASM Bibliography

An annotated bibliography of papers which deal with or use Abstract State Machines (ASMs), as of January 1998.Comment: Also maintained as a BibTeX file at http://www.eecs.umich.edu/gasm

Dimensions of web site credibility and their relation to active trust and behavioural impact

This paper discusses two trends that threaten to undermine the effectiveness of online social marketing interventions: growing mistrust and competition. As a solution, this paper examines the relationships between Web site credibility, target audiences’ active trust and behaviour. Using structural equation modelling to evaluate two credibility models, this study concludes that Web site credibility is best considered a three-dimensional construct composed of expertise, trustworthiness and visual appeal, and that trust plays a partial mediating role between Web site credibility and behavioural impacts. The paper examines theoretical implications of conceptualizing Web sites according to a human credibility model, and factoring trust into Internet-based behavioural change interventions. Practical guidelines suggest ways to address these findings when planning online social marketing interventions

Computer‐based interactive tutorial versus traditional lecture for teaching introductory aspects of pain

In the health sciences, a wide range of computer‐based courseware is now available. The aim of the study described in this paper has been to compare the effectiveness of a computer‐based learning (CBL) software package and a traditional lecture (TL) for the delivery, of introductory material on pain. Nineteen undergraduate nursing students were divided into two groups to attend a one‐hour learning session which introduced clinical aspects of pain and which was delivered by either CBL or TL. Students were assessed for prior knowledge by a pre‐session test, and for knowledge gain by an identical post‐session test. In addition, a multiple‐choice question paper was used to examine differences in pain knowledge between the two groups, and a questionnaire was used to examine the students’ views on their experience during the learning session. The results demonstrated that both groups showed significant knowledge gain after their respective learning sessions. No significant differences between the groups in the magnitude of knowledge gain were found for clinical aspects of pain delivered during the learning sessions. The attitude questionnaire revealed that students attending CBL reported similar learning experiences to those attending the lecture

Quantum Bounded Query Complexity

We combine the classical notions and techniques for bounded query classes with those developed in quantum computing. We give strong evidence that quantum queries to an oracle in the class NP does indeed reduce the query complexity of decision problems. Under traditional complexity assumptions, we obtain an exponential speedup between the quantum and the classical query complexity of function classes. For decision problems and function classes we obtain the following results: o P_||^NP[2k] is included in EQP_||^NP[k] o P_||^NP[2^(k+1)-2] is included in EQP^NP[k] o FP_||^NP[2^(k+1)-2] is included in FEQP^NP[2k] o FP_||^NP is included in FEQP^NP[O(log n)] For sets A that are many-one complete for PSPACE or EXP we show that FP^A is included in FEQP^A[1]. Sets A that are many-one complete for PP have the property that FP_||^A is included in FEQP^A[1]. In general we prove that for any set A there is a set X such that FP^A is included in FEQP^X[1], establishing that no set is superterse in the quantum setting.Comment: 11 pages LaTeX2e, no figures, accepted for CoCo'9

Human Resource Information Systems for Competitive Advantage: Interviews with Ten Leaders

[Excerpt] Increasingly, today\u27s organizations use computer technology to manage human resources (HR). Surveys confirm this trend (Richards-Carpenter, 1989; Grossman and Magnus, 1988; Human Resource Systems Professionals 1988; KPMGPeat Marwick, 1988). HR professionals and managers routinely have Personnel Computers (PCs) or computer terminals on their desks or in their departments. HR computer applications, once confined to payroll and benefit domains, now encompass incentive compensation, staffing, succession planning, and training. Five years ago, we had but a handful of PC-based software applications for HR management. Today, we find a burgeoning market of products spanning a broad spectrum of price, sophistication, and quality (Personnel Journal, 1990). Top universities now consider computer literacy a basic requirement for students of HR, and many consulting firms and universities offer classes designed to help seasoned HR professionals use computers in their work (Boudreau, 1990). Changes in computer technology offer expanding potential for HR management (Business Week, 1990; Laudon and Laudon, 1988)