The Tyler Statesman (1975)

The first official newspaper of the institution, it describes the early classes, events, and scholarships on the campus. Articles include: Dr. D.M. Anthony Named Academic Vice President; Blood Bank Drive May 7; 142 to Receive Degrees at May 17 Commencement; Blood Drive Set May 7; Seniors- Time is Near!; Letter to the Editor; Job Search Barometer; Library Expands; Loans Available Through Veterans Regional Office; Powell Resigns; Theatre Class Sets Program; Campus Work Progressing; Students Use Computer in Management Courses; Test Scoring Made Easier by Means of Opscan 17; Dr. Roddy Re-elected; Students at TSC with TAWP Staff; Student Services News; MBA OKed For School; Department of Chemistry has Own Clinical Program; Dr. Clopper Gets Post; Computer Programs Due Enlargment; Dr. Stewart Reappointed; TSC Campus Security Responsibilities Increase Due to Expanding Facilities; Five Take SFA Trip; Dr. Glenn Williams Wins Art Award; Construction Manual Ready; TSC Prof Recieves CPA; PE Meet Here; First Honor Roll Released; Dr. Spurgin Heads SWISA; Mrs. Benton Presents Paper in Malakoff; TSC Hosts Regional PE Meet; Summer Class Schedules are Given; Exam Schedule; Funding Approvedhttps://scholarworks.uttyler.edu/tylerstatesman/1006/thumbnail.jp

Characterizing the strongly jump-traceable sets via randomness

We show that if a set $A$ is computable from every superlow 1-random set, then $A$ is strongly jump-traceable. This theorem shows that the computably enumerable (c.e.) strongly jump-traceable sets are exactly the c.e.\ sets computable from every superlow 1-random set. We also prove the analogous result for superhighness: a c.e.\ set is strongly jump-traceable if and only if it is computable from every superhigh 1-random set. Finally, we show that for each cost function $c$ with the limit condition there is a 1-random $\Delta^0_2$ set $Y$ such that every c.e.\ set $A \le_T Y$ obeys $c$. To do so, we connect cost function strength and the strength of randomness notions. This result gives a full correspondence between obedience of cost functions and being computable from $\Delta^0_2$ 1-random sets.Comment: 41 page

On characters of Chevalley groups vanishing at the non-semisimple elements

Let G be a finite simple group of Lie type. In this paper we study characters of G that vanish at the non-semisimple elements and whose degree is equal to the order of a maximal unipotent subgroup of G. Such characters can be viewed as a natural generalization of the Steinberg character. For groups G of small rank we also determine the characters of this degree vanishing only at the non-identity unipotent elements.Comment: Dedicated to Lino Di Martino on the occasion of his 65th birthda

Fuzzy Least Squares Twin Support Vector Machines

Least Squares Twin Support Vector Machine (LST-SVM) has been shown to be an efficient and fast algorithm for binary classification. It combines the operating principles of Least Squares SVM (LS-SVM) and Twin SVM (T-SVM); it constructs two non-parallel hyperplanes (as in T-SVM) by solving two systems of linear equations (as in LS-SVM). Despite its efficiency, LST-SVM is still unable to cope with two features of real-world problems. First, in many real-world applications, labels of samples are not deterministic; they come naturally with their associated membership degrees. Second, samples in real-world applications may not be equally important and their importance degrees affect the classification. In this paper, we propose Fuzzy LST-SVM (FLST-SVM) to deal with these two characteristics of real-world data. Two models are introduced for FLST-SVM: the first model builds up crisp hyperplanes using training samples and their corresponding membership degrees. The second model, on the other hand, constructs fuzzy hyperplanes using training samples and their membership degrees. Numerical evaluation of the proposed method with synthetic and real datasets demonstrate significant improvement in the classification accuracy of FLST-SVM when compared to well-known existing versions of SVM

-Generic Computability, Turing Reducibility and Asymptotic Density

Generic computability has been studied in group theory and we now study it in the context of classical computability theory. A set A of natural numbers is generically computable if there is a partial computable function f whose domain has density 1 and which agrees with the characteristic function of A on its domain. A set A is coarsely computable if there is a computable set C such that the symmetric difference of A and C has density 0. We prove that there is a c.e. set which is generically computable but not coarsely computable and vice versa. We show that every nonzero Turing degree contains a set which is not coarsely computable. We prove that there is a c.e. set of density 1 which has no computable subset of density 1. As a corollary, there is a generically computable set A such that no generic algorithm for A has computable domain. We define a general notion of generic reducibility in the spirt of Turing reducibility and show that there is a natural order-preserving embedding of the Turing degrees into the generic degrees which is not surjective