Lớp nâng cao nghiệp vụ hành chính văn phòng, soạn thảo văn bản và văn thư lưu trữ sẽ diễn ra từ thứ 2 - thứ 7 (23/7/2012-28/7/2012) tại phòng D301b - Trường ĐH KHXH và NV TP HCM (10-12 Đinh Tiên Hoàng, P Bến Nghé, Q.1, TP HCM). Lễ khai giảng sẽ được tổ chức lúc 8h ngày thứ 2 23/7/2012 cũng tại phòng D301b. Các học viên đăng ký tham gia lớp học vui lòng đến làm thủ tục nhập học, đóng học phí và nhận tài liệu học tập từ 7h-7h50 tại phòng D301b.Lịch học cụ thể:Thứ, ngày Nội dung chuyên đề PhòngSố tiếtGiảng viênThứ Hai23/7Sáng + Chiều: Chuyên đề 1: Kỹ thuật soạn thảo văn bản trong các cơ quan, doanh nghiệp Phòng D.301b10- Ban tổ chức lớp học- TS. Lê Văn In GVCC, nguyên Phó Hiệu trưởng Trường Cán bộ Tp. HCMThứ Ba24/7Sáng: - Chuyên đề 2: Những vấn đề cơ bản về quản lý nhà nước và CCHC trong công tác văn thư, lưu trữ- Chuyên đề 3: Tập huấn về Luật Lưu trữ/2011 và các văn bản mới về văn thư, lưu trữ05TS. Nghiêm Kỳ Hồng Trưởng Bộ môn Lưu trữ học và QTVPChiều: -Chuyên đề 3: (tiếp theo)-Chuyên đề 4: Giới thiệu về ứng dụng Công nghệ 5S của Nhật Bản trong văn thư, lưu trữ 05Thứ Tư25/7Sáng + Chiều: Chuyên đề 5: Tổ chức quản lý văn bản trong các cơ quan, doanh nghiệp10ThS. Đỗ Văn Học Phó Trưởng Khoa Lịch sửThứ Năm26/7Sáng + Chiều: Chuyên đề 6: Ứng dụng CNTT và áp dụng hệ thống quản lý chất lượng (ISO) trong công tác văn phòng, văn thư và lưu trữ10ThS. Đỗ Văn Thắng, Phó GĐ Trung tâm tin học, Trường Đại học KHXH & NV Thứ Sáu27/7Sáng + Chiều: Chuyên đề 7: Một số nghiệp vụ cơ bản trong công tác lưu trữ (thu thập, xác định giá trị và chỉnh lý tài liệu lưu trữ) 10TS. Phan Đình NhamCVCC, nguyên Giám đốc TTLTQG IIThứ Bảy28/7Sáng: Chuyên đề 8: Nghiệp vụ thư ký văn phòng chuyên nghiệp10h30: Tổng kết lớp học, trao chứng chỉ 05ThS. Nguyễn Văn Báu,Giảng viên Bộ mônLưu trữ học và QTVP- Ban tổ chức lớp họcGhi chú:- Buổi sáng: từ 7h30’ đến 11h00’- Buổi chiếu: từ 13h30’ đến 16h30’Thông tin chi tiết vui lòng liên hệ: Cô Phương Quỳnh Sđt: 0902.622.044 – Email: phuongquynh.pn@gmail.com- 7h: Làm thủ tục tiếp nhận học viên- 8h: Khai giảng (15 phút) TRƯỜNG ĐẠI HỌC GTVT PHÂN HIỆU TẠI TP HỒ CHÍ MINH Số: CỘNG HÒA XÃ HỘI CHỦ NGHĨA VIỆT NAM Độc lập - Tự - Hạnh phúc Tp.Hồ Chí Minh, ngày 01 tháng 08 năm 2017 / TB-ĐHGTVT-PH.HCM LỊCH HỌC LẠI CỦA ĐỢT ĐĂNG KÝ THÁNG 07/2017 HỆ CAO HỌC (*) Lưu ý: - Lịch áp dụng cho học viên đăng ký học lại tháng 07/2017; - Lịch thi thông báo sau; - Đề nghị giảng viên lấy danh sách học lại trước bắt đầu giảng dạy phòng P10-D3 Phòng Đào tạo; - Thời khóa biểu môn học lại cập nhật sau STT TÊN MÔN Tiếng Anh TC Nơi nhận: - Ban Giám đốc; - Thông báo HV, đăng website; - Lưu Đào tạo, TCHC SL LỚP HỌC LẠI NGÀY BẮT ĐẦU HỌC Các lớp Cao học từ K23.2 20 06/08/2017 đến K24 NGÀY KẾT THÚC HỌC BUỔI HỌC PHÒNG HỌC GIÁO VIÊN 13/08/2017 Tối ngày tuần; Thứ Chủ nhật học sáng chiều 402 C2 Cô Thanh TL.GIÁM ĐỐC KT TRƯỞNG PHÒNG ĐÀO TẠO PHÓ TRƯỞNG PHÒNG (đã ký) ThS Trần Phong Nhã AVM Description Compilation using Types as Modes Gerald Penn Department of Computer Science University of Toronto gpenn@cs.toronto.edu Abstract This paper provides a method for generat- ing compact and efficient code to imple- ment the enforcement of a description in typed feature logic. It does so by view- ing information about types through the course of code generation as modes of in- stantiation — a generalization of the com- mon practice in logic programming of the hi nary instantiated/variable mode decl ara- tions that advanced Prolog compilers use. Section 1 introduces the description lan- guage. Sections 2 and 3 motivate the view of mode and compilation taken here, and outline a mode declaration language for typed feature logic. Sections 4 through 7 then present the compiler. An evaluation on two grammars is presented at the end. 1 Descriptions The logic of typed feature structures (Carpenter, 1992) has been widely used as a means of formal- izing and developing natural language grammars, notably in Head-driven Phrase Structure Gram- mar (Pollard and Sag, 1994). These grammars are stated using a vocabulary consisting of a fi- nite meet semi-lattice of types and a set of fea- tures that must be specified for each grammar, and this vocabulary must obey certain rules. A set of appropriateness conditions must specify, for each feature, which types of feature structures may bear it, and which types of values it may take. Unique feature introduction states that every feature has a least type that bears it, called its introducer. The effect of these rules is that typed feature structures (TFSs) can be described using a very terse descrip- tion language. A TFS that matches the description NUMBER : singular, for example, might implic- itly be of a type index, which introduces NUMBER. From that, we can deduce that the TFS also bears values for PERSON and GENDER, with particular appropriate values, because those features are in- troduced by the same type. Terse descriptions al- low us to work with very large TFSs conveniently. Given this basic vocabulary, descriptions can be used in implicational constraints that encode prin- ciples of grammar. These are often restricted to the form T 0, where T is a type, and 0 is a description. They also appear in several control strategies that are used to combine TFSs, such as extended phrase structure rules for parsing or gen- eration (Wintner, 1997; Malouf et al., 2000), or resolution with a Prolog-like relational language (Carpenter and Penn, 1996; Makino et al., 1998). While description languages vary, they are usu- ally restricted to a subset of the following: Definition: The set of descriptions over a count- able set of types, T, a finite set of features, Feat, and a countable set of variables, Var, is the small- est set Desc that contains: • Var, • zX,allX E Var, • T, • 7F : ch, all 71 E Feat * , 0 E Desc, and • A V), V 11), all 0,'O E Desc. Variables are used to enforce sharing of struc- ture among substructures, and are often used with 275 wider scope than a single TFS to pass structure — for example, from daughter categories to mother categories in phrase structure rules or between ar- guments in definite clause relations. With inequa- tions X), they can also be used to prohibit structure sharing. Preceding a description with a feature path, 7r, causes that description to be en- forced on the substructure at the end of that path. 2 Types as Modes What makes descriptions so terse, and what distin- guishes the logic of typed feature structures from more general order-sorted terms or record struc- tures, is their strong notion of typing. Types intro- duce features, types determine the arity (number of features) of a TFS, types are the antecedents to grammar constraints and BioMed Central Page 1 of 5 (page number not for citation purposes) Virology Journal Open Access Short report Avian influenza: genetic evolution under vaccination pressure Magdalena Escorcia 1 , Lourdes Vázquez 1 , Sara T Méndez 2 , Andrea Rodríguez- Ropón 3 , Eduardo Lucio 3 and Gerardo M Nava* 1,4 Address: 1 Departamento de Producción Animal Aves. Facultad de Medicina Veterinaria y Zootecnia. Universidad Nacional Autónoma de México, D. F. 04510, México, 2 Unidad de Genética de la Nutrición. Instituto Nacional de Pediatría, D. F, 04530, México, 3 Investigación Aplicada, S. A. de C. V. 7 Norte 416, Tehuacán, Puebla, 75700, México and 4 Laboratory of Mucosal Biology. University of Illinois at Urbana-Champaign, 61801, USA Email: Magdalena Escorcia - magdaescorcia@exalumno.unam.mx; Lourdes Vázquez - lourdesvh_98@hotmail.com; Sara T Méndez - saratm@correo.unam.mx; Andrea Rodríguez-Ropón - ropon67@yahoo.com.mx; Eduardo Lucio - elucio@grupoidisa.com; Gerardo M Nava* - gerardomnava@gmail.com * Corresponding author Abstract Antigenic drift of avian influenza viruses (AIVs) has been observed in chickens after extended vaccination program, similar to those observed with human influenza viruses. To evaluate the evolutionary properties of endemic AIV under high vaccination pressure (around 2 billion doses used in the last 12 years), we performed a pilot phylogenic analysis of the hemagglutinin (HA) gene of AIVs isolated from 1994 to 2006. This study demonstrates that Mexican low pathogenicity (LP) H5N2-AIVs are constantly undergoing genetic drifts. Recent AIV isolates (2002–2006) show significant molecular drifts when compared with the H5N2 vaccine-strain or other field isolates (1994–2000). This study also demonstrates that molecular drifts in the HA gene lineages follow a yearly trend, suggesting gradually cumulative sequence mutations. These findings might explain the increasing incidence of LP H5N2 AIV isolated from commercial avian farms. These findings support recent concerns about the challenge of AIV antigenic drift and influenza epidemics. Findings Avian influenza virus (AIV) is a member of the Orthomyxo- viridae family, Influenzavirus A genus. AIV is characterized by its ability to undergo constant antigenic changes [1]. AIV envelope contains two major glycoproteins, hemag- glutinin (HA) and neuraminidase (NA) [2]. The HA/NA proteins play a key role during cellular infection. Different HA/NA combinations allow AIV subtype discrimination. Depending on the damage caused to avian species, AIVs are categorized as either high or low pathogenicity (HP and LP, respectively). In Mexico, LP AIV was first detected in May 1994, among commercial farms. Since then, an Avian Influenza National Campaign established by the Mexican Ministry of Agriculture, Livestock, Rural Development, Fisheries and Food (SAGARPA, its Spanish acronym), is in opera- tion. The purpose of this campaign is to eradicate the sub- type H5N2 LP AIV that is still present in specific areas of Mexico. Vaccination of commercial flocks is one of many strategies for this campaign. The vaccine strain officially authorized, as seed for commercial vaccine production is the A/Ck/México/CPA-232/94 (H5N2), isolated in 1994 [3]. The use of the commercial vaccine in Mexico was origi- nally aimed to eradicate HP AIV and this was accom- plished in June 1994. Then, the decision was made to Published: 24 January 2008 Virology Journal 2008, 5:15 doi:10.1186/1743-422X-5-15 Received: 5 December 2007 Accepted: 24 January 2008 This article is available from: http://www.virologyj.com/content/5/1/15 © 2008 Escorcia et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any RESEARCH Open Access Average bit error probability for the l-MRC detector under Rayleigh fading Mitchell Omar Calderon Inga and Gustavo Fraidenraich * Abstract In this paper, an exact expression for the average bit error probability was obtained for the l-MRC detector, proposed in Sendonaris et al. (IEEE Trans Commun 51: 1927-1938, IEEE Trans. Commun 51: 1939-1948), under Rayleigh fading channel. In addition, a very accurate approximation was obtained to calculate the average bit error probability for any power allocation scheme. Our expressions allow to investigate the possible gains and situations where cooperation can be beneficial. Keywords: User cooperation, Virtual MIMO, Bit error probability, Rayleigh fading I. Introduction Diversity t echniques have been widely accepted as one of effective ways of combat multipath fading in w ireless communications [1], in particular spatial diversity is spe- cially effective at mitigating these multipath situation. However, in many wireless applications, the use of mul- tiple antennas is not practi cal due to size and cost lim- itations of the termi nals. One possible way to have diversity without increasing the number of antennas is through the use of cooperative diversity. Cooperative diversity has root in classical information the ory work on relay channels [2], [3]. Cooperative net- works achieve diversity gain by allowing the users to cooperate, and thus, each wirelessuserisassumedto transmit data as well as act as a cooperative agent for another user [4], [5]. The first implementation strategy for cooperation was introduced in [1], [6], where the achievable rate region, outage probability, and coverage area were analyzed. In this pioneering work, assumin g a suboptimal recei- ver called l-MRC, the bit e rror probability was com- puted assuming a fixed channel. This kind of receiver combines the signal from the first period of transmis- sion with the signal transmitted jointly by the both users in the second period of transmission. The variable lÎ[0,1] establishes the degree of confidence in the bits estimate d by the partner. For situations where th e inter- user channel presents favorable condi tio ns, the variable l should be close to unity; on the other h and, for very severe channels conditions, the parameter l should tend to zero. Unfortunately, the bit error probability was computed only f or a fixed channel and remained open for the situation where all the fading coefficients are Rayleigh distributed. In this paper, an exact and approximate expression is computed for the average bit error probability assuming a Rayleigh fading for the inter-user channel and for the direct channel between users and base station (BS). II. System Model This section summarizes the system model t hat was employed in [1], [6]. A. System Model The channel model used in [6] can be mathematically expressed as Y 0 ( t ) = K 10 X 1 ( t ) + K 20 X 2 ( t ) + Z 0 ( t ) (1) Y 1 ( t ) = K 21 X 2 ( t ) + Z 1 ( t ) (2) Y 2 ( t ) = K 12 X 1 ( t ) + Z 2 ( t ) (3) where Y 0 (t), Y 1 (t), and Y 2 (t) are the baseband models of the received signal at the BS, user 1, and user 2, respectively, during one symbol period. Also, X i (t)isthe signal transmitted by user i under power constraint P i , for i =1,2,andZ i (t) are white zero-mean Gaussian noise random processes with spectral height N i /2 for i * Correspondence: