U.S. Department of Justice OMB No. 1121-0329 Office of Justice Programs Bureau of Justice Assistance The U.S. Department of Justice (DOJ), Office of Justice Programs (OJP), Bureau of Justice Assistance (BJA) is seeking applications from local and tribal partners to plan, implement, and enhance place-based, community-oriented strategies to address neighborhood-level crime issues as a component of or a foundation to a broader neighborhood revitalization or redevelopment initiative. Byrne Criminal Justice Innovation (BCJI) resources will target locations where a significant proportion of crime occurs as compared to the overall jurisdiction. BCJI furthers the Department’s mission by leading efforts to enhance the capacity of local and tribal communities to effectively target and address significant crime issues through collaborative cross-sector approaches that help advance broader neighborhood development goals. Byrne Criminal Justice Innovation Program FY 2013 Competitive Grant Announcement Eligibility Eligible entities to serve as fiscal agent include states, unit of local governments, non-profit organizations (including tribal non-profit organizations), and federally recognized Indian tribal governments as determined by the Secretary of the Interior. Recognizing that community safety is essential to neighborhood revitalization, BCJI resources are targeted specifically at persistently distressed neighborhoods that have significant crime challenges that generate a significant proportion of crime or type of crime within the larger community or jurisdiction impeding broader neighborhood development goals. The BCJI application requires a consortium of partners (hereinafter referred to as “cross-sector partnership”) to work together to design a strategy addressing a targeted crime problem and respond to the scope of this solicitation. The application must also show commitment from the local law enforcement agency, community leaders, and a research partner as part of this cross- sector partnership through detailed letters of support outlining their participation and partnership in the project. This cross-sector partnership must designate one agency or organization as the fiscal agent. Throughout this solicitation, “fiscal agent” and “applicant” are used interchangeably. The fiscal agent will serve as the BCJI applicant and submit the application on behalf of the cross-sector partnership, oversee coordination of the cross-sector partnership if funds are awarded, and manage any subawards for services. The fiscal agent will be legally responsible for complying with all applicable federal rules and regulations in receiving and expending federal funds. The application must demonstrate that the fiscal agent has the capacity, commitment, and community support to serve as fiscal agent. The fiscal agent must demonstrate such capacity by showing experience engaging residents as well as core criminal justice and other partners in the implementation of community justice plans, especially in the targeted community. The application must contain a strategy that responds to the scope and requirements of this solicitation. BJA-2013-3472 OMB No. 1121-0329 Approval Expires 02/28/2013 2 Jurisdictions are strongly encouraged to seek the support of their local U.S. Attorney and local policymakers. BJA may elect to make awards for applications submitted under this solicitation in future fiscal years, dependent on the merit of the applications and on the availability of appropriations. Deadline Applicants must register with Grants.gov prior to submitting an application. (See “How To Apply,” page 35.) All applications are due by 11:59 p.m. eastern time on March 4, 2013. (See “Deadlines: Registration and Application,” page 5.) KWEF-AIT Research Grant 2016 (KARG 2016) Background Kurita Water and Environmental Foundation (KWEF) is a public interest incorporated foundation aiming at contribution to the development of new technology of water and environmental protection Since it was established in 1997, about 800 grants were awarded out of total application of about 6,000 with total amount of the grants of about 500 m Japanese Yen The KWEF, in collaboration with Asian institute of Technology (AIT), has launched a new research grant program (KWEF-AIT Research Grant, KARG) for young researchers mainly in emerging countries in South East Asia Purpose KARG aims to promote human resource development through researches to solve water and/or environmental problems in South East Asia The focal research area in 2016 is water-related Environmental Science and Technology Total grant amount in 2016 Three million Japanese yen in total for ca 16 projects (max 300,000 Japanese yen each) Target countries in 2016 Thailand, Indonesia, and Vietnam 2016 Research Period st From September , 2016 st To August 31 , 2017 The Best Researcher Selection and Invitation to Japan KWEF will invite the best researcher among the 2016 awardees to Tokyo, in August 2018, to give invited lectures and visit laboratories based on the 2016 Research outcomes to be selected by the KARG selection committee in January 2018 th th Note: 2014 Awardee invited lectures: August 25 -26 , 2016 (venue in Tokyo) Definition of young researcher Less than or equal to 40 years old in principle (PhD candidates are also encouraged to apply.) Pre-screening in each country Pre-screening will be done in respective countries The contact points are: For Thailand, Dr Chart Chiemchaisri, Kasetsart University, fengccc@ku.ac.th For Indonesia, Prof Tjandra Setiadi, Institut Teknologi Bandung, tjandra@che.itb.ac.id For Vietnam, Dr Nguyen Viet-Anh, Hanoi University of Civil Engineering, anhnv@nuce.edu.vn Application form (see attached) The application form may be down loaded at http://karg.ait.ac.th/application.html All application forms should be sent to the KARG-secretariat (KARG-sec@ait.asia) as well as the th respective contact points, by e-mail, by May 30 , 2016, for Indonesia or Vietnam, and by the end of May st (May 31 , 2016) for Thailand Vietnam contact point: Assoc Prof Nguyen Viet-Anh, Director, Institute of Environmental Science and Engineering (IESE), Head of Water Supply and Sanitation Division, Hanoi University of Civil Engineering, Vietnam E-mail: anhnv@nuce.edu.vn; vietanhctn@yahoo.com; Tel +84-4-38691604; MP: +84-913209689 Member of the international selection committee Prof Chongrak Polprasert (Chair), Thammasat University, Thailand Assoc Prof Chart Chiemchaisri (General Secretary), Kasetsart University, Thailand Prof Tjandra Setiadi, Institut Teknologi Bandung, Indonesia Assoc Prof Nguyen Viet-Anh, Hanoi University of Civil Engineering, Vietnam Prof Motoyuki Suzuki, Representative of KWEF Prof Kazuo Yamamoto, Representative of AIT Member of the national selection committees Thailand (hosted by Kasetsart University) Prof Chongrak Polprasert (Chair), Thammasat University Assoc Prof Chart Chiemchaisri (Secretary), Kasetsart University Assoc Prof Suwasa Kantawanichkul, Chiangmai University Assoc.Prof Udomphon Puetpaiboon, Prince of Songkla University Assoc Prof Thammarat Koottatep, Asian Institute of Technology Assoc Prof Chawalit Rattanatamskul, Chulalongkorn University Indonesia (hosted by Institut Teknologi Bandung) Prof Tjandra Setiadi (Chair), Institut Teknologi Bandung Prof Yulinah Trihadiningrum, Institut Teknologi Sepuluh November Prof Setijo Bismo, Unversitas Indonesia Assoc Prof Agus Jatnika Effendi, Institut Teknologi Bandung Vietnam (hosted by Hanoi University of Civil Engineering) Assoc Prof Dr Nguyen Viet-Anh (Chair), Hanoi University of Civil Engineering Assoc Prof Dr Nguyen Phuoc Dan, Ho Chi Minh University of Technology Assoc Prof Nguyen Van Cong, Can Tho University Assoc Prof Tran Van Quang, Da Nang University of Technology Due Dates Open for application: st th st st April – May 30 , 2016 (Indonesia and Vietnam); April – May 31 , 2016 (Thailand) Pre-screening in each country: by the international selection committee meetings th The international selection committee meeting: June 10 , 2016 th Final Approval by the KWEF Board: July , 2016 Result notification: by the end of July, 2016 th Award ceremony: August 19 , 2016 (venue in Indonesia) U.S. Department of Justice OMB No. 1121-0329 Office of Justice Programs Bureau of Justice Assistance The U.S. Department of Justice (DOJ), Office of Justice Programs (OJP), Bureau of Justice Assistance (BJA) is seeking applications for funding to establish or enhance drug court services, coordination, offender management, and recovery support services. This program furthers the Department’s mission by providing resources to state, local, and tribal governments and state, local, and tribal courts to enhance drug court programs and systems for nonviolent substance- abusing offenders. Adult Drug Court Discretionary Grant Program FY 2013 Competitive Grant Announcement Eligibility For Category 1: Implementation and Category 2: Enhancement, applicants are limited to states, state and local courts, counties, units of local government, and Indian tribal governments (as determined by the Secretary of the Interior). For Category 3: Statewide, applicants are limited to state agencies such as the State Administering Agency (SAA), the Administrative Office of the Courts, and the state Alcohol and Substance Abuse Agency. Note: Applicants must demonstrate that eligible drug court participants promptly enter the drug court program following a determination of their eligibility. A required initial period of incarceration will be grounds for disqualification unless the period of incarceration is mandated by statute for the offense in question. In such instances, the applicant must demonstrate the offender is receiving treatment services while incarcerated if available and begins drug court treatment services immediately upon release. Note: BJA may elect to make awards for applications submitted under this solicitation in future fiscal years, dependent on the merit of the applications and on the availability of appropriations. Deadline Applicants must register with Grants.gov prior to submitting an application. (See “How To Apply,” page 29.) All applications are due by 11:59 p.m. eastern time on February 21, 2013. (See “Deadlines: Registration and Application,” page 4.) BJA-2013-3418 OMB No. 1121-0329 Approval Expires 02/28/2013 2 Contact Information For technical assistance with submitting the application, contact Grants.gov Customer Support Hotline at 1–800–518–4726 or 606–545–5035, or via e-mail to support@grants.gov . Note: The Grants.gov Support Hotline hours of operation are 24 hours a day, seven days a week, except federal holidays. For assistance with any other requirement of this solicitation, contact the BJA Justice Information Center at 1–877–927–5657, via e-mail to JIC@telesishq.com, or by live web chat . The BJA Justice Information Center hours of operation are 8:30 a.m. to 5:00 p.m. eastern time, Monday through Friday, and 8:30 a.m. to 8:00 p.m. eastern time on the solicitation close date. Grants.Gov number assigned to announcement: BJA-2013-3418 Release date: December 18, 2012 BJA-2013-3418 OMB No. 1121-0329 Approval Expires 02/28/2013 3 CONTENTS Overview 4 Deadlines: Registration and Application 4 Eligibility 4 Adult Drug Court Discretionary Grant Program—Specific Information 4 Performance Measures 13 Notice of Post-Award FFATA Reporting Requirement 14 What an Application Should Include 14 Information to Complete the Application for Federal Assistance (SF-424) Abstract Program Narrative Budget Detail Worksheet and Budget Narrative Indirect Cost Rate Agreement (if applicable) Tribal Authorizing Resolution (if applicable) Additional Attachments Other Standard Forms Selection Criteria 20 Review Process 27 Additional Requirements 28 How To Apply 29 Provide Feedback to OJP on This Solicitation 31 Application Hindawi Publishing Corporation Fixed Point Theory and Applications Volume 2011, Article ID 232163, 15 pages doi:10.1155/2011/232163 Research Article A Hybrid-Extragradient Scheme for System of Equilibrium Problems, Nonexpansive Mappings, and Monotone Mappings Jian-Wen Peng, 1 Soon-Yi Wu, 2 and Gang-Lun Fan 2 1 School of Mathematics, Chongqing Normal University, Chongqing 400047, China 2 Department of Mathematics, National Cheng Kung University, Tainan 701, Taiwan Correspondence should be addressed to Jian-Wen Peng, jwpeng6@yahoo.com.cn Received 21 October 2010; Accepted 24 November 2010 Academic Editor: Jen Chih Yao Copyright q 2011 Jian-Wen Peng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. We introduce a new iterative scheme based on both hybrid method and extragradient method for finding a common element of the solutions set of a system of equilibrium problems, the fixed points set of a nonexpansive mapping, and the solutions set of a variational inequality problems for a monotone and k-Lipschitz continuous mapping in a Hilbert space. Some convergence results for the iterative sequences generated by these processes are obtained. The results in this paper extend and improve some known results in the literature. 1. Introduction In this paper, we always assume that H is a real Hilbert space with inner product ·, · and induced norm ·and C is a nonempty closed convex subset of H, S : C → C is a nonexpansive mapping; that is, Sx − Sy≤x − y for all x,y ∈ C, P C denotes the metric projection of H onto C,andFixS denotes the fixed points set of S. Let {F k } k∈Γ be a countable family of bifunctions from C × C to R, where R is the set of real numbers. Combettes and Hirstoaga 1 introduced the following system of equilibrium problems: finding x ∈ C, such that ∀k ∈ Γ, ∀y ∈ C, F k x, y ≥ 0, 1.1 where Γ is an arbitrary index set. If Γ is a singleton, the problem 1.1 becomes the following equilibrium problem: finding x ∈ C, such that F x, y ≥ 0, ∀y ∈ C. 1.2 2 Fixed Point Theory and Applications The set of solutions of 1.2 is denoted by EPF. And it is easy to see that the set of solutions of 1.1 can be written as k∈Γ EPF k . Given a mapping T : C → H,letFx, yTx,y − x for all x, y ∈ C. Then, the problem 1.2 becomes the following variational inequality: finding x ∈ C, such that Tx,y − x ≥ 0, ∀y ∈ C. 1.3 The set of solutions of 1.3 is denoted by VIC, A. The problem 1.1 is very general in the sense that it includes, as special cases, optimization problems, variational inequalities, minimax problems, Nash equilibrium problem in noncooperative games, and others; see, for instance, 1–4. In 1953, Mann 5 introduced t he following iteration algorithm: let x 0 ∈ C be an arbitrary point, let {α n } be a real sequence in 0, 1, and let the sequence {x n } be defined by x n1 α n x n 1 − α n Sx n . 1.4 Mann iteration algorithm has been extensively investigated for nonexpansive mappings, for example, please see 6, 7. Takahashi et al. 8 modified the Mann iteration method 1.4 and introduced the following hybrid projection algorithm: x 0 ∈ H, C 1 C, x 1 P C 1 x 0 , y n α n x n 1 − α n Sx n , C n1 z ∈ C n : y Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2010, Article ID 158395, 11 pages doi:10.1155/2010/158395 Research Article A Multifactor Extension of Linear Discriminant Analysis for Face Recognition under Varying Pose and Illumination Sung Won Park and Marios Savvides Electrical and Computer Engineering Department, Carnegie Mellon University, 5000 Forbes Avenue Pittsburgh, PA 15213, USA Correspondence should be addressed to Sung Won Park, sungwonp@cmu.edu Received 11 December 2009; Revised 27 April 2010; Accepted 20 May 2010 Academic Editor: Robert W. Ives Copyright © 2010 S. W. Park and M. Savvides. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Linear Discriminant Analysis (LDA) and Multilinear Principal Component Analysis (MPCA) are leading subspace methods for achieving dimension reduction based on supervised learning. Both LDA and MPCA use class labels of data samples to calculate subspaces onto which these samples are projected. Furthermore, both methods have been successfully applied to face recognition. Although LDA and MPCA share common goals and methodologies, in previous research they have been applied separately and independently. In this paper, we propose an extension of LDA to multiple factor frameworks. Our proposed method, Multifactor Discriminant Analysis, aims to obtain multilinear projections that maximize the between-class scatter while minimizing the withinclass scatter, which is the same core fundamental objective of LDA. Moreover, Multifactor Discriminant Analysis (MDA), like MPCA, uses multifactor analysis and calculates subject parameters that represent the characteristics of subjects and are invariant to other changes, such as viewpoints or lighting conditions. In this way, our proposed MDA combines the best virtues of both LDA and MPCA for face recognition. 1. Introduction Face recognition has significant applications for defense and national security. However, today, face recognition remains challenging because of large variations in facial image appearance due to multiple factors including facial feature variations among different subjects, viewpoints, lighting conditions, and facial expressions. Thus, there is great demand to develop robust face recognition methods that can recognize a subject’s identity from a face image in the presence of such variations. Dimensionality reduction techniques are common approaches applied to face recog- nition not only to increase efficiency of matching and compact representation, but, more importantly, to highlight the important characteristics of each face image that provide discrimination. In particular, dimension reduction methods based on supervised learning have been proposed and commonly used in the foll ow ing manner. Given a set of face images with class labels, dimension reduction methods based on supervised learning make full use of class labels of these images to learn each subject’s identity. Then, a generalization of this dimension reduction is achieved for unlabeled test images, also called out-of-sample images. Finally, these test images are classified with respect to different subjects, and the classification accuracy is computed to evaluate the effectiveness of the discrimination. Hindawi Publishing Corporation Fixed Point Theory and Applications Volume 2009, Article ID 374815, 32 pages doi:10.1155/2009/374815 Research Article A Hybrid Extragradient Viscosity Approximation Method for Solving Equilibrium Problems and Fixed Point Problems of Infinitely Many Nonexpansive Mappings Chaichana Jaiboon and Poom Kumam Department of Mathematics, Faculty of Science, King Mongkut’s University of Technology Thonburi, Bangkok 10140, Thailand Correspondence should be addressed to Poom Kumam, poom.kum@kmutt.ac.th Received 25 December 2008; Accepted 4 May 2009 Recommended by Wataru Takahashi We introduce a new hybrid extragradient viscosity approximation method for finding the common element of the set of equilibrium problems, the set of solutions of fixed points of an infinitely many nonexpansive mappings, and the set of solutions of the variational inequality problems for β-inverse-strongly monotone mapping in Hilbert spaces. Then, we prove the strong convergence of the proposed iterative scheme to the unique solution of variational inequality, which is the optimality condition for a minimization problem. Results obtained in this paper improve the previously known results in this area. Copyright q 2009 C. Jaiboon and P. Kumam. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 1. Introduction Let H be a real Hilbert space, and let C be a nonempty closed convex subset of H. Recall that a mapping T of H into itself is called nonexpansive see 1 if Tx − Ty≤x − y for all x, y ∈ H. We denote by FT{x ∈ C : Tx x} the set of fixed points of T. Recall also that a self-mapping f : H → H is a contraction if there exists a constant α ∈ 0, 1 such that fx − fy≤αx − y, for all x, y ∈ H. In addition, let B : C → H be a nonlinear mapping. Let P C be the projection of H onto C. The classical variational inequality which is denoted by VIC, B is to find u ∈ C such that Bu, v − u ≥ 0, ∀v ∈ C. 1.1 2 Fixed Point Theory and Applications For a given z ∈ H, u ∈ C satisfies the inequality u − z, v − u ≥ 0, ∀v ∈ C, 1.2 if and only if u P C z. It is well known that P C is a nonexpansive mapping of H onto C and satisfies x − y, P C x − P C y ≥ P C x − P C y 2 , ∀x, y ∈ H. 1.3 Moreover, P C x is characterized by the following properties: P C x ∈ C and for all x ∈ H, y ∈ C, x − P C x, y − P C x ≤ 0, 1.4 x − y 2 ≥ x − P C x 2 y − P C x 2 . 1.5 It is easy to see that the following is true: u ∈ VI C, B ⇐⇒ u P C u − λBu ,λ>0. 1.6 One can see that the variational inequality 1.1 is equivalent to a fixed point problem. The variational inequality has been extensively studied in literature; see, for instance, 2– 6. This alternative equivalent formulation has played a significant role in the studies of the variational inequalities and related optimization problems. Recall the following. 1 A mapping B of C into H is called monotone if Bx − By, x − y ≥ 0, ∀x, y ∈ C. 1.7 2 A mapping B is called β-strongly monotone see 7, 8 if there exists a constant β>0 such that Bx − By, x − y ≥ β x − y 2 , ∀x, y ∈ C. 1.8 3 A mapping B is called k-Lipschitz continuous if there ... be sent to the KARG- secretariat (KARG- sec@ait.asia) as well as the th respective contact points, by e-mail, by May 30 , 2016, for Indonesia or Vietnam, and by the end of May st (May 31 , 2016) ... point: Assoc Prof Nguyen Viet-Anh, Director, Institute of Environmental Science and Engineering (IESE), Head of Water Supply and Sanitation Division, Hanoi University of Civil Engineering, Vietnam... Effendi, Institut Teknologi Bandung Vietnam (hosted by Hanoi University of Civil Engineering) Assoc Prof Dr Nguyen Viet-Anh (Chair), Hanoi University of Civil Engineering Assoc Prof Dr Nguyen