Digital Commons Network^™

Philanthropy And The Climate Crisis: Learning And Evaluation To Drive Decision-Making And Identify Emergent Opportunities, Lindsay Hanson, Rosy Kalfus, Courtney Lee

The Foundation Review

To us, strategic learning is an adaptive approach to using evaluation and other data to directly affect decision-making and action.

An early focus on building relationships and accountability to specific outcomes and values — including establishing baselines and plans for regular reporting and interpretation — laid the groundwork for decision-making in later stages of the Climate Solutions program’s lifecycle.

Increasingly rapid data feedback loops informed the Climate Solutions program’s strategy pivot, decisions, and collaboration with grantees and funder partners.

Engagement in strategic learning and use of evaluation to drive decision-making improved with practice, as illustrated by the Climate Solutions team’s …

More Than The Sum: A Collective Vision For The Future Of Strategy, Monitoring, Impact, Learning And Evaluation (Smile) In Climate Philanthropy, Marta Arranz, Rees Warne, Olivia Deich, Amelia Abdelrazik

The Foundation Review

Organizations funding climate work must learn quickly and make urgent decisions despite uncertainties and low levels of control. Within climate philanthropy, sharing learnings widely and using evidence for decision-making are crucial.

The authors argue the “evaluation” field is both misdefined and underleveraged. In a shift away from accountability and siloed learning within organizations, they propose redefining the evaluation profession as SMILE (Strategy, Monitoring, Impact, Learning, and Evaluation).

After three years of building field-wide learning infrastructure, the authors reflect on the field’s progress and offer recommendations to the climate philanthropy ecosystem.

Climate Breakthrough's Impact And Learning System: A Case Study, Olivia Deich

The Foundation Review

Climate Breakthrough makes one-time, multi-million-dollar, multi-year, flexible grants to climate strategists. The portfolio is collectively aimed at achieving an outsized emissions reduction goal. There are no strategy pillars, and grantees are from across the globe. This model, paired with Climate Breakthrough’s guiding values, opens the door for impact and learning work focused on iteration and learning.

In practice, grantees identify a small set of key performance indicators themselves; they share emissions reduction estimates for their work that are important but not dominant; they have abundant impact and learning resources; and the funder gains a wealth of data from which to …

Feedback Loops In Practice: A Case Study On Evaluating A Climate Collaborative, Mansi Shah, Amy Sherwood, Abbie Turiansky, Drew Koleros, Axum Teferra

The Foundation Review

Philanthropic support to address the climate crisis has grown substantially, yet it remains unclear how effectively philanthropies are learning from their investments, from each other, and from other actors about what generates meaningful impact. Evaluations have come under scrutiny, as conventional approaches often struggle to account for complexity and provide the timely insights needed for adaptive management.

In this article, the authors present the learning journey of a complex, systems-focused climate philanthropy initiative that uses structured feedback loops as an evaluation design. They describe how these loops were implemented over a two-year evaluation; discuss the choice of complexity-aware methods; and …

Spend-Down To Scale Up: Limited-Life Giving In The Climate Crisis, Madeleine C. Mckinnon, Samuel Rogers, David Gunsberg, Emma Mcintosh

The Foundation Review

This article shares first-hand experiences of a charitable foundation operating under a spend-down model, illustrating how a fixed time horizon shapes philanthropic and programmatic behavior. The authors discuss three conditions that a spend-down horizon reliably forces: the imperative to fund quickly, collaboratively, and boldly on shared goals; the discipline to concentrate capital with strategic focus; and the emphasis on learning and collaboration as both a means to optimize for impact now and to sustain and scale impact over the long term.

Authors explore the influence of these conditions in a series of case studies working towards a clean energy transition …

A Word From The Writing Team (October 2026), Pam Walter, Mfa, Laura Deloretta, Phd

A Word From the Writing Team (Newsletter)

No abstract provided.

Leader-Follower Formation-Based Leader Velocities Estimation Via Adaptive-Τ Tustin Differentiator, Zeyad A. Karam, Mohammed Y. Hassan, Amjad J. Humaidi

Iraqi Journal of Computers, Communications, Control and Systems Engineering

This work develops a leader–follower formation for differential-drive mobile robots with an explicit estimator for the leader's velocities. Firstly, a leader robot position-variance-adaptive, under-rate-limited differentiator provides forward speed and yaw-rate estimate for the leader velocities, using exponentially weighted increment variances that drive a convex one-sided mapping to provide adaptive time constants for this estimator. Secondly, the control stack couples three layers: first layer, a nonlinear body-frame kinematic law for leader tracking, with orientation corrections handled via a smooth bounded function sin(eθ)/eθ to eliminate singularities near zero error. Second layer, a formation-preserving follower controller based on …

Adaptive Intelligent H-Infinity Controller Design For Mimo Nonlinear Systems Under Asymmetric Input Saturation, Mohammed Qasim, Hazem I. Ali, Omar Farouq Lutfy

Iraqi Journal of Computers, Communications, Control and Systems Engineering

This paper details the design of a robust adaptive intelligent guaranteed cost H-infinity controller, tailored for MIMO nonlinear systems subject to external disturbances, parametric uncertainties, and asymmetric input saturation constraints. The adaptive intelligent part of the proposed controller consists of a Radial Basis Function Neural Network (RBFNN) with bounded output to respect saturation constraints and a robust adaptive law for RBFNN weights estimation. This part serves to estimate the system's uncertain nonlinearities and external disturbances. The guaranteed cost H-infinity is designed based on Linear Matrix Inequalities (LMIs) to address the system parameter uncertainties and bounded RBFNN estimation errors, as well …

Enhancing Gru With Long-Short Attention: A Case Study Of Saudi Stock Market Prediction, Hussein Samma, Qusay Shihab Hamad, Ali Salem Bin Sama, Adnan Bakather, Khaled Alhashash

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Predicting stock market movements accurately is a challenging task due to the inherent complexity and volatility of financial markets. In recent years, deep learning techniques, particularly the Gated Recurrent Unit (GRU), have shown promising results in financial time series prediction. However, capturing the most relevant information from large volumes of data remains a critical challenge for improving prediction accuracy. This work introduces an attention-enhanced GRU model for forecasting the Saudi stock market. The proposed model integrates attention mechanisms to dynamically prioritize different input patterns, enabling the network to focus on the most relevant information for prediction. Two types of attention …

Generative Artificial Intelligence-Driven Augmentation With Deep Feature Fusion Model For Rare Disease Detection And Classification, V. Kavitha

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Rare disease detection focuses on identifying rare health conditions that affect a tiny fraction of people. Detection is challenging because symptoms are often ambiguous and information is limited. In recent years, retinal diseases have become a serious problem worldwide. Progressing a computer-assisted diagnosis (CAD) method is highly beneficial and functional for ophthalmologists. Proper detection and treatment can save eye vision. Deep learning (DL) has advanced across various scientific fields and is leveraged for numerous healthcare tasks. This research presents a Generative Artificial Intelligence-Assisted Adaptive Feature Fusion Network for Rare Retinal Disease Detection (GAIAFF-RRDD) technique assists ophthalmologists by allowing early and …

Power-Efficient Target Tracking And Coverage In Under-Provisioned Wireless Visual Sensor Networks, Muna M. Jawad

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Due to their ability to detect the physical environment, directional sensors have attracted a lot of attention in wireless visual sensor networks (WVSN). These sensors perform two key functions: communication and sensing. A WVSN comprises numerous configurable limited fields of view sensors, comprising distinct angular sectors, arranged with multiple targets randomly scattered in the same surrounding region. Therefore, there is a critical need to improve the network's lifetime and reduce power demand while providing complete target coverage. This paper looks at under-resourced visual networks with an inadequate number of sensors to match applications' needs and develops a viable model to …

Fractal Circularly Polarized Leaky-Wave Antenna For X-Band Cubesat Communication, Ghufran Kh. Mahmood, Ahmed M A Sabaawi

Iraqi Journal of Computers, Communications, Control and Systems Engineering

This study presents the design and optimization of a circularly polarized fractal leaky-wave antenna (LWA) designed for X-band CubeSat communication systems. The proposed antenna is based on a via-less substrate-integrated waveguide (SIW) structure. It utilizes composite right-/left-handed (CRLH) transmission-line principles to achieve a high-impedance boundary and enhanced radiation performance. The work focuses on optimizing the antenna structure for operation at 8 GHz by investigating the effects of key design parameters, including the slot width (W_s), bent length (L_s1), inter-slot spacing (d_slot), and number of periodic unit cells (n). Antenna performance is evaluated in terms …

Improving Performance For Dco-Ofdm Based Vlc Via Convolutional Coding And Viterbi Decoding, Maha F. Shatti, Samir M. Hameed, Atheer A. Sabri

Iraqi Journal of Computers, Communications, Control and Systems Engineering

The reliability of Visible Light Communication (VLC) is affected by several parameters, the most significant being high peak-to-average power ratio(PAPR) and nonlinear distortion. This study presents an adaptive direct current O-OFDM (DCO-OFDM) based VLC system as a solution, which integrates error correction the Convolutional coding and Viterbi decoding (by hard and soft decision methods) with a PAPR reduction technique that combines Vandermonde-like Matrix (VLM) precoding with a nonlinear companding transform (NCT). This proposed system enhances resistance to channel impairments, thereby reducing BER while maintaining the gains of PAPR reduction. Moreover, examined the system under realistic VLC propagation conditions both Line …

Cost-Efficient High-Capacity Radio Over Fiber (Rof) Transmission: Integrating Coarse And Dense Wdm Techniques, Hilal A. Fadhil, Fadia N. Hummadi, Feras N. Hasoon, Haider J. Abd, Hussein A. Kazem

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Using Radio over Fiber (RoF) has expanded lately to the point where a key component of it link between central office and base station would be useful from the whole industry. As the market grows towards communication products of ultra-high-speed, like 5G applications, capital expenditure (CapEx) is crucial. The two primary types regarding wavelength division multiplexing (WDM) techniques Dense WDM and Coarse WDM are integrated in the presented work to create cost-effective, new design paradigm for RoF. The suggested system is tested and put into use at 10 Gbps data transmission rate. In addition, it describes how the two systems-based …

A Triple-Verification Framework For Swift, Real-Time Detection Of Anomalous Sensor Readings In Large-Scale Iot Systems, Taha E. Al-Jarakh, Inas Jawad Kadhim, Ayad Al-Dujaili, Eduardo Campos Mercado

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Due to the massive expansion of Internet of Things systems and the variety of anomalous data resulting from faulty sensors, cyberattacks, or communication failures, it has become difficult to handle this type of data. Although current machine learning and statistical analysis techniques offer high accuracy in detecting anomalies, these methods alone are not sufficient for handling massive amounts of data in real-time. Therefore, the idea arose to propose a Triple-Verification Framework to detect and block anomalous data. The first stage of the framework acts as a firewall to block incoming messages from blocklisted/unauthorized sensors or carrying unknown schemes. In the …

Energy-Efficient Resource Allocation In Cloud Service Management Via Significant Feature Ranking With Recurrent Network Model, C. Arun, S. Santhoshkumar, J. Jegathesh Amalraj, T. Suresh

Iraqi Journal of Computers, Communications, Control and Systems Engineering

The increasing adoption of cloud computing (CC) produces a notable growth in data centres, resulting in severe financial, environmental, and operational problems. To mitigate these issues, energy-efficient resource allocation strategies have been developed as a key solution for enhancing energy utilization while ensuring high performance and reliability. In this framework, machine learning (ML) enables the implementation of dynamic and intelligent approaches for effective resource utilization. In this paper, we focus on the Scalable Hybrid Feature Ranking Framework for Energy-Efficient Resource Allocation (SHFRF-EERA) approach in Cloud Service Management Systems. The novelty of the proposed model lies in the integration of hybrid …

A Corpus Linguistics-Driven Hybrid Deep Representation Framework Incorporating Majority Voting For Enhanced Automatic Spoken Language Identification, Lubin Balasubramanian, J. Uthayakumar, Niranjana Kumara M, Sariga Arjunan

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Spoken Language Identification (SLID) is a well-researched area. It has previously been recognized as a crucial first stage in every multi-lingual speech recognition system. Latest developments in artificial intelligence (AI) and deep learning (DL) are used to highly strengthen the performance of SLID systems, allowing them to perform a crucial part in mainstream applications The gathered speaker utterances have been entered into the DL network for training phase. The language equivalent to the great posterior probability is then recognized as the target language. This study introduces an Enhancing Automatic Spoken Language Identification with Corpus Linguistics and Ensemble Deep Representation (EASLI-CLEDR) …

Learning Opportunities 2026/2027, Illinois Math And Science Academy

Course Catalogs

The graduation requirements of the Illinois Mathematics and Science Academy are established by the IMSA Board of Trustees. Each semester, students must take a minimum of five academic courses (2.5 credits) for a letter grade (not Pass/Fail), not including Fine Arts or Wellness courses. Students may enroll in a maximum of eight academic opportunities each semester, including academic courses, Fine Arts and Wellness courses, and Experiential programs. The College and Academic Counselor approves enrollment for students in all courses and experiences.

Richmond Law Magazine: Autumn 2026

Richmond Law Magazine

To Lead is to Empower

The House That Family Money Built

The Front Line of Virginia's Judicial Systen

A Profile Of Assisted Living Direct Care Workforce Training Requirements Across The United States, Erh-Chi Hsu, Paula Carder, Lindsey Smith, Zhiqing E. Zhou, Olga Yakusheva, Anna S. Beeber, Eric Jutkowitz, Kali Thomas

Institute on Aging Publications

Objectives

To characterize assisted living (AL) direct care worker (DCW) training requirements across the United States and how these regulations have changed over time. Specifically, we examine state-level profiles of training regulations, including duration, frequency, content, source of materials, evaluation, and changes in regulatory coverage.

Design

Cross-sectional and longitudinal descriptive study using state policy data and AL directories from 2019, 2021, and 2023.

Setting and Participants

All US states' AL training–related regulations; all ALs and AL beds governed by those regulations.

Methods

We used a mixed-methods approach with an explanatory sequential design (QUAN → qual), first conducting health services regulatory …

Check Out The Library, 2026 Fall Issue, Cal Poly Humboldt Library

Library Publications

Issue 21

Montana Kaimin, October 1, 2026, Students Of The University Of Montana, Missoula

Montana Kaimin, 1898-present

Student newspaper of the University of Montana, Missoula.

Introduction

Spiritan Horizons

No abstract provided.

Fr. Henri Le Floch Cssp—The Forgotten Pioneer Of Poullart Studies. Part I, Eamonn Mulcahy Cssp

Spiritan Horizons

No abstract provided.

How The Spiritan Mission And Spirituality Can Bring Hope Today, Igono Abel Raphael Cssp

Spiritan Horizons

No abstract provided.

A Spirit-Led Movement: From Missionary Sending To Lay Vocation: The Development Of Lay Spiritans In The United States (1965–2026), John Hansen Phd, Anne Marie Witchger Hansen Phd

Spiritan Horizons

No abstract provided.

The Dynamics Of Hospitality: A Paradigm For Promoting And Doing Authentic Catholic Theologies, Gregory Olikenyi Cssp

Spiritan Horizons

No abstract provided.

Bede Uche Ukwuije, Trinity And Inculturation: The Humanity Of God And The Future Of African Theolog Y. University Of Notre Dame Press, 2026. X + 351 Pages. $65 (Hardcover); $51.99 (Ebook), George Worgul

Spiritan Horizons

No abstract provided.

From Homes To Classrooms: Cultural Wisdom As A Guide For Stem Lesson Planning, Miriam Ortiz, Uma Ganesan, Angela Chapman, William Medina-Jerez, Ruby Lynch Arroyo, Mourat Tchoshanov

Teaching and Learning Faculty Publications

This article describes innovative elementary science instructional approaches based on cultural wisdom developed by preservice teachers enrolled in a teacher preparation program at a university in the U.S.-Mexico border region. As a part of a larger study, three Latina preservice elementary teachers were a part of a teacher residency in conducting community interviews and reflection activities to uncover cultural backgrounds that could inform culturally relevant STEM lesson planning, centering on family and home knowledge. This project began with family interviews during winter break and culminated in lesson planning and implementation during their science methods course in the spring semester. The …

October 2026 Library & Learning Newsletter, Minnesota State University, Mankato. Library & Learning Dean's Office Communication Team

Library & Learning Newsletters

PDF version of the October 2026 (Volume 5, Issue 2) Library & Learning Newsletter.