作者：
HERR, DONALDBLUMENSTOCK, NORMANHONORARY MEMBERTHE AUTHORS MR. HERR
Honorary Member of the A.S.N.E. has the B.S. in E.E. M.S. in E.E. and E.E. degrees. He was National Coffin Foundation Fellow of the General Electric Company National Tau Beta Pi Fellow and National Sigma Tau Fellow at the Moore School of Electrical Engineering University of Pennsylvania and at M.I.T. prior to World War II. He was also awarded a National Gordon McKay Fellowship by Harvard University and received the A. Atwater Kent Award in Electrical Engineering from the University of Pennsylvania. A licensed radio amateur at 12 Mr. Herr first worked summers at RCA and Bell Laboratories and was with the General Electric Company in 1939 and 1940 as development engineer before volunteering for over five years of active Naval duty. He served as Officer-in-Charge Electrical Minesweeping Group Bureau of Ships December 1940 to April 1943 as Acting Design Superintendent and Officer-in-Charge
Los Angeles-Long Beach Harbor Surge Investigation U. S. Naval Shipyard Terminal Island to November 1944 and as Research-Patents Liaison Officer
Office of Naval Research to January 1946 returning to inactive duty as lieutenant commander U.S.N.R. Mr. Herr received two Navy letters of commendation. Since 1946 he was assistant to vice president in charge of the engineering division of Control Instrument Company Brooklyn New York and is project engineer at the Reeves Instrument Corporation responsible for new servo and computer component developments. Mr. Herr has been associated with Dean Harold Pender and Professor Ernst Guillemin in advanced network theory and has specialized for 12 years in development and design of servomechanisms differential analyzers computers and fire control systems utilizing advanced network analysis and synthesis methods. Mr. Herr is also presently teaching servomechanisms network-synthesis and feedback amplifier design in the Graduate School of the Polytechnic Institute of Brooklyn. He has contributed frequently to the JOURNAL OF THE AMERICA
This volume contains the proceedings of the second joint PAPM-PROBMIV Workshop, held at the University of Copenhagen, Denmark, July 25–26, 2002 as part of the Federated Logic Conference (FLoC 2002). The PAPM-PROBMIV ...
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ISBN:
(数字)9783540456056
ISBN:
(纸本)9783540439134
This volume contains the proceedings of the second joint PAPM-PROBMIV Workshop, held at the University of Copenhagen, Denmark, July 25–26, 2002 as part of the Federated Logic Conference (FLoC 2002). The PAPM-PROBMIV workshop results from the combination of two wo- shops: PAPM (Process Algebras and Performance Modeling) and PROBMIV (Probabilistic methods in Veri?cation). The aim of the joint workshop is to bring together the researchers working across the whole spectrum of techniques for the modeling, speci?cation, analysis, and veri?cation of probabilistic systems. Probability is widely used in the design and analysis of software and hardware systems, as a means to derive e?cient algorithms (e.g. randomization), as a model for unreliable or unpredictable behavior (as in the study of fault-tolerant systems and computer networks), and as a tool to study performance and - pendability properties. The topics of the workshop include speci?cation, m- els, and semantics of probabilistic systems, analysis and veri?cation techniques, probabilistic methods for the veri?cation of non-probabilistic systems, and tools and case studies. The ?rst PAPM workshop was held in Edinburgh in 1993; the following ones were held in Regensberg (1994), Edinburgh (1995), Turin (1996), Enschede (1997), Nice (1998), Zaragoza (1999), and Geneva (2000). The ?rst PROBMIV workshop was held in Indianapolis, Indiana (1998); the next one took place in Eindhoven (1999). In 2000, PROBMIV was replaced by a Dagstuhl seminar on Probabilistic methods in Veri?cation.
Recently, emotion analysis and classification of tweets have become a crucial area of research. The Arabic language had experienced difficulties with emotion classification on Twitter(X), needing preprocessing more th...
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Recently, emotion analysis and classification of tweets have become a crucial area of research. The Arabic language had experienced difficulties with emotion classification on Twitter(X), needing preprocessing more than other languages. Emotion detection is a major challenge in Natural Language Processing (NLP), which allows machines to ascertain the emotions expressed in the text. The task includes recognizing and identifying human feelings such as fear, anger, sadness, and joy. The discovered sentiments and feelings expressed in tweets have gained much recognition in recent years. The Arab region has played a substantial role in international politics and the global economy needs to scrutinize the emotions and sentiments in the Arabic language. Lexicon-based and machine-learning techniques are two common models that address the problems of emotion classification. This study introduces a Chimp Optimization Algorithm with a Deep Learning-Driven Arabic Fine-grained Emotion Recognition (COADL-AFER) technique. The presented COADL-AFER technique mainly aims to detect several emotions in Arabic tweets. In addition to its academic significance, the COADL-AFER technique has practical applications in various fields, including enhancing applications of E-learning, aiding psychologists in recognising terrorist performance, improving product quality, and enhancing customer service. The COADL-AFER technique applies the long short-term memory (LSTM) model for emotion detection. Finally, the hyperparameter selection of the LSTM method can be accomplished by COA. The experimental validation of the COADL-AFER system, a crucial step in our research, is verified utilizing the Arabic tweets dataset. The simulation results stated the betterment of the COADL-AFER technique, further reinforcing the reliability of our research.
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