Hasil untuk "Communities. Classes. Races"

Bo Leng, Weiqi Zhang, Zhuoren Li et al.

Reinforcement learning has demonstrated significant potential in the field of autonomous driving. However, it suffers from defects such as training instability and unsafe action outputs when faced with autonomous racing environments characterized by high dynamics and strong nonlinearities. To this end, this paper proposes a trajectory guidance and dynamics constraints Reinforcement Learning (TraD-RL) method for autonomous racing. The key features of this method are as follows: 1) leveraging the prior expert racing line to construct an augmented state representation and facilitate reward shaping, thereby integrating domain knowledge to stabilize early-stage policy learning; 2) embedding explicit vehicle dynamic priors into a safe operating envelope formulated via control barrier functions to enable safety-constrained learning; and 3) adopting a multi-stage curriculum learning strategy that shifts from expert-guided learning to autonomous exploration, allowing the learned policy to surpass expert-level performance. The proposed method is evaluated in a high-fidelity simulation environment modeled after the Tempelhof Airport Street Circuit. Experimental results demonstrate that TraD-RL effectively improves both lap speed and driving stability of the autonomous racing vehicle, achieving a synergistic optimization of racing performance and safety.

Ashkan Jafari Fesharaki, Yasser Mestrah, Ibrahim Hemadeh et al.

This paper studies a feedback driven configuration tuning framework for adaptive sensing feedback in Integrated Sensing and Communication (ISAC) systems. We propose a framework in which the User Equipment (UE) adapts sensing parameters under dynamic conditions while satisfying network defined constraints. The problem is formulated as a stochastic constrained optimization problem, to improve sensing reliability and latency. We consider a bistatic ISAC sensing feedback setup and instantiate the framework via threshold optimization as a representative case study, enabling benchmarking against baseline methods. To ensure efficiency under UE computational limits, we propose Ranking Aware, Constrained, and Efficient CMAES (RACE CMA), which integrates two stage racing, common random numbers, noise aware ranking, and feasible constraint handling. Results show that the proposed approach improves sensing reliability by about 35 percent while reducing computational cost by about 25 percent, yielding roughly a twofold gain in performance cost efficiency. This highlights that UE side configuration tuning is a promising mechanism for enhancing closed loop ISAC performance under practical system constraints.

Bewketu Mamaru Mengiste, Yitayal Addis Alemayehu, Gebrie Tsegaye Mersha et al.

Building sustainable cities and communities (SDG 11) is one of the 17 Sustainable Development Goals (SDGs), with urban walkability emerging as a basic urban planning strategy to create more livable cities. This study aimed to identify and summarize the drivers of urban walkability, ultimately contributing to the livable city’s agenda by influencing the perception of both the community and policymakers. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) criteria, along with the eye-balling method, were employed to identify and evaluate key research papers on urban walkability. A total of 45 drivers were identified and grouped into four categories: socio-demographic, eco-infrastructural, biophysical, and policy and planning- based on thematic similarities, suitable in serving as a framework to strengthen sector-based actions and collaborations vital especially to developing regions. The findings also indicated that leveraging the drivers can improve societal and policymakers perception, attitude, and technical capacity, fostering sustainable actions toward urban walkability. For effective and sustainable actions, the framework should be tailored and used in developing countries based on their context. Moreover, the classification framework on urban walkability drivers provides a strong foundation for future research in developing nations aiming to create livable cities.

Rebecca Gjini, Matthias Morzfeld, Oliver R. A. Dunbar et al.

Ensemble Kalman methods were initially developed to solve nonlinear data assimilation problems in oceanography, but are now popular in applications far beyond their original use cases. Of particular interest is climate model calibration. As hybrid physics and machine-learning models evolve, the number of parameters and complexity of parameterizations in climate models will continue to grow. Thus, robust calibration of these parameters plays an increasingly important role. We focus on learning climate model parameters from minimizing the misfit between modeled and observed climate statistics in an idealized setting. Ensemble Kalman methods are a natural choice for this problem because they are derivative-free, scalable to high dimensions, and robust to noise caused by statistical observations. Given the many variants of ensemble methods proposed, an important question is: Which ensemble Kalman method should be used for climate model calibration? To answer this question, we perform systematic numerical experiments to explore the relative computational efficiencies of several ensemble Kalman methods. The numerical experiments involve statistical observations of Lorenz-type models of increasing complexity, frequently used to represent simplified atmospheric systems, and some feature neural network parameterizations. For each test problem, several ensemble Kalman methods and a derivative-based method "race" to reach a specified accuracy, and we measure the computational cost required to achieve the desired accuracy. We investigate how prior information and the parameter or data dimensions play a role in choosing the ensemble method variant. The derivative-based method consistently fails to complete the race because it does not adaptively handle the noisy loss landscape.

Runhao Jiang, Renchi Yang, Wenqing Lin

Social recommendation, which seeks to leverage social ties among users to alleviate the sparsity issue of user-item interactions, has emerged as a popular technique for elevating personalized services in recommender systems. Despite being effective, existing social recommendation models are mainly devised for recommending regular items such as blogs, images, and products, and largely fail for community recommendations due to overlooking the unique characteristics of communities. Distinctly, communities are constituted by individuals, who present high dynamicity and relate to rich structural patterns in social networks. To our knowledge, limited research has been devoted to comprehensively exploiting this information for recommending communities. To bridge this gap, this paper presents CASO, a novel and effective model specially designed for social community recommendation. Under the hood, CASO harnesses three carefully-crafted encoders for user embedding, wherein two of them extract community-related global and local structures from the social network via social modularity maximization and social closeness aggregation, while the third one captures user preferences using collaborative filtering with observed user-community affiliations. To further eliminate feature redundancy therein, we introduce a mutual exclusion between social and collaborative signals. Finally, CASO includes a community detection loss in the model optimization, thereby producing community-aware embeddings for communities. Our extensive experiments evaluating CASO against nine strong baselines on six real-world social networks demonstrate its consistent and remarkable superiority over the state of the art in terms of community recommendation performance.

Emran Yasser Moustafa, Ivana Dusparic

Autonomous vehicles have shown promising potential to be a groundbreaking technology for improving the safety of road users. For these vehicles, as well as many other safety-critical robotic technologies, to be deployed in real-world applications, we require algorithms that can generalize well to unseen scenarios and data. Model-based reinforcement learning algorithms (MBRL) have demonstrated state-of-the-art performance and data efficiency across a diverse set of domains. However, these algorithms have also shown susceptibility to changes in the environment and its transition dynamics. In this work, we explore the performance and generalization capabilities of MBRL algorithms for autonomous driving, specifically in the simulated autonomous racing environment, Roboracer (formerly F1Tenth). We frame the head-to-head racing task as a learning problem using contextual Markov decision processes and parameterize the driving behavior of the adversaries using the context of the episode, thereby also parameterizing the transition and reward dynamics. We benchmark the behavior of MBRL algorithms in this environment and propose a novel context-aware extension of the existing literature, cMask. We demonstrate that context-aware MBRL algorithms generalize better to out-of-distribution adversary behaviors relative to context-free approaches. We also demonstrate that cMask displays strong generalization capabilities, as well as further performance improvement relative to other context-aware MBRL approaches when racing against adversaries with in-distribution behaviors.

Anggun Nadia Fatimah, Alfina Rahmah Dewi, Lydia Prifta Siagian

Posisi website sekolah merupakan hal yang vital tidak hanya untuk kepentingan publikasi kegiatan, melainkan juga sebagai sarana promosi khususnya bagi sekolah swasta yang pendanaan utamanya diperoleh dari siswa. Dalam konteks SMKS Al Ittihad Cianjur, website sekolah nampaknya belum optimal dilirik sebagai aset kehumasan yang penting bagi sekolah. Solusi untuk permasalahan yang diajukan penulis adalah pelatihan keterampilan jurnalistik daya bagi siswa dan mengaktifkan kembali website sekolah untuk sarana publikasi dan promosi. Kegiatan pelatihan ini dikemas dalam bentuk workshop meliputi presentasi materi dasar dan pengerjaan praktik lapangan. Pelatihan ini berperan mengukuhkan fondasi keterampilan jurnalistik siswa. Dengan skema ini, diharapkan para peserta dapat terus menumbuhkembangkan keterampilan menulis yang telah ia miliki, dan sekolah memiliki lebih banyak sumber daya manusia yang dapat diaktivasi untuk mengaktivasi web sekolah dan meningkatkan kredibilitas sekolah di mata publik.

Viani Naufalia

The objective of this research is to find out how the determinants of market conduct monitoring contribute to fostering customer trust and security, supported by the mediating variable customer satisfaction index. The researcher used quantitative research methods from customers of financial service products in DKI Jakarta, then data analysis techniques used SMART PLS 4.0 application and CSI score calculations. The results of this research show that market conduct monitoring has a significant positive determination in increasing customer confidence by 50.2% and customer sense of security by 25.2%, and can be mediated by a customer satisfaction index of 31.4%.

Kianoush Hasani

<p>Memorial architectural textures do not emerge in isolation; rather, they are shaped by a multitude of factors, both seen and unseen, that interconnect in a complex chain of causality. By meticulously tracing and contextualizing these factors, we can aspire to imbue them with a sense of immortality, embedding them within specific contexts and decoding their significance. This study endeavors to advance the understanding of contemporary Iranian monumental architecture through the lens of shape grammar, exploring how this grammar can inform the creation of new designs within this architectural tradition. By delving into the theoretical frameworks of memorial architecture and grammatical form, this article not only offers a framework for the perpetuation of this architectural heritage but also lays the groundwork for systematic evaluation. The objectives of this study are twofold: To perceive contemporary Iranian monumental architecture through the extraction of fundamental shapes within the grammar of form. To generate new designs that uphold the essence of contemporary Iranian monuments. This research adopts an applied approach, utilizing documentary-analytical methods as its primary research methodology. Both library and field methods have been employed for data collection. The process of data analysis involves identifying the grammar of form, which serves as a production system for generating new designs from basic shapes according to a set of rules. By applying this method to analyze six contemporary Iranian monuments, basic shapes are extracted, and a set of rules is formulated. Subsequently, new designs, infused with the essence of the selected monuments, are created. In conclusion, by employing the grammar technique of shape within the context of six contemporary monuments and devising an algorithm comprising a finite set of basic shapes and instructions, this study demonstrates the potential for generating an infinite array of design solutions.</p>

Kyoungtae Ji, Sangjae Bae, Nan Li et al.

This paper presents a game-theoretic strategy for racing, where the autonomous ego agent seeks to block a racing opponent that aims to overtake the ego agent. After a library of trajectory candidates and an associated reward matrix are constructed, the optimal trajectory in terms of maximizing the cumulative reward over the planning horizon is determined based on the level-K reasoning framework. In particular, the level of the opponent is estimated online according to its behavior over a past window and is then used to determine the trajectory for the ego agent. Taking into account that the opponent may change its level and strategy during the decision process of the ego agent, we introduce a trajectory mixing strategy that blends the level-K optimal trajectory with a fail-safe trajectory. The overall algorithm was tested and evaluated in various simulated racing scenarios, which also includes human-in-the-loop experiments. Comparative analysis against the conventional level-K framework demonstrates the superiority of our proposed approach in terms of overtake-blocking success rates.

Maximilien Dreveton, Charbel Chucri, Matthias Grossglauser et al.

The metric backbone of a weighted graph is the union of all-pairs shortest paths. It is obtained by removing all edges $(u,v)$ that are not the shortest path between $u$ and $v$. In networks with well-separated communities, the metric backbone tends to preserve many inter-community edges, because these edges serve as bridges connecting two communities, but tends to delete many intra-community edges because the communities are dense. This suggests that the metric backbone would dilute or destroy the community structure of the network. However, this is not borne out by prior empirical work, which instead showed that the metric backbone of real networks preserves the community structure of the original network well. In this work, we analyze the metric backbone of a broad class of weighted random graphs with communities, and we formally prove the robustness of the community structure with respect to the deletion of all the edges that are not in the metric backbone. An empirical comparison of several graph sparsification techniques confirms our theoretical finding and shows that the metric backbone is an efficient sparsifier in the presence of communities.

Kehinde Samuel ALEHILE

Climate change poses mounting risks to agricultural development and rural livelihoods in Nigeria. This study investigates the impacts of climate change on agricultural sector employment in Nigeria. Agriculture provides income and sustenance for much of Nigeria’s rural population. However, smallholder rain-fed farming predominates, with minimal resilience to climate shifts. Historical data reveal rising temperatures and declining, erratic rainfall across Nigeria’s agro-ecological zones since the 1970s. Crop modeling predicts further climate changes will reduce yields of key staple crops. This threatens the viability of smallholder agriculture and risks widespread job losses. The study adopts a nonlinear autoregressive distributed lag (NARDL) modeling approach to evaluate climate change effects on agricultural sector employment in Nigeria from 1990 to 2020. Findings reveal reduced rainfall initially raises employment, as farming requires more labor in dry conditions. However, protracted droughts significantly reduce agricultural jobs. Increased temperatures consistently lower farm employment through reduced yields and incomes. Based on these findings, the study recommends that adaptive strategies are urgently needed to build resilience, promote climate-smart agriculture, and safeguard rural livelihoods.

Germán Héctor González , Elena V. Elena V. Sapir , Alexander D. Vasilchenko

Экономические изменения вследствие глобального финансового кризиса 2009 г., пандемии COVID-19, сбоев в цепочках поставок и других потрясений привели к радикальной трансформации производственного ландшафта. Возник вопрос относительно сравнительных преимуществ парадигм глобальных производственных сетей (ГПС) и глобальных цепочек создания стоимости (ГЦСС) в анализе международного производства. В связи с этим была проверена гипотеза, предполагающая, что концепция ГПС позволяет лучше идентифицировать сдвиги, возникающие в международных производственных структурах, при этом выявляются региональные модели сотрудничества. В первом разделе рассмотрены основные методологические ограничения концепции ГЦСС, а также изложены причины применения сетевого подхода к анализу международного производства. Для подтверждения теоретических предположений во втором разделе была исследована сфера автомобилестроения в Европейском союзе. При сравнении количественных инструментов ГПС и ГЦСС был достигнут возможный компромисс, заключающийся в расчете сетевых показателей (транзитивность, центральность и т. д.) с использованием межстрановых таблиц «затраты — выпуск». В результате исследования поставленная гипотеза была подтверждена. В частности, показатель центральности продемонстрировал положительный эффект от вступления в ЕС для Чехии и Словакии, тогда как ни один из индикаторов ГЦСС не показал подобных сдвигов. В то же время индикаторы ГЦСС отметили влияние кризиса 2008 г., тогда как сетевые показатели свидетельствуют об отсутствии структурных изменений в производственной системе в исследуемый период. Полученные данные подтверждают теоретическое сопоставление подходов ГПС и ГЦСС. Методологическое единство двух наборов показателей позволило шире взглянуть на европейскую региональную интеграцию ядра и периферии и динамику сетей автомобилестроения. Результаты исследования могут быть использованы для переосмысления процессов региональной интеграции как в Европе, так и в Латинской Америке и Евразии.

Cynthia S. Deale

This case study describes a semester-long project completed by 46 undergraduate college students involved in courses in tourism planning and marketing, our community partner, and me the instructor.

Jennifer Shutek

First paragraphs: Candan Turkkan’s Feeding Istanbul: The Political Economy of Urban Provisioning begins with an intimate anecdote about her grandmother’s experi­ences of hunger during the Second World War and the centrality of bread in her family. She reflects on the fragility of food systems that belie appearances of food abundance in urban areas and the lasting psychological impacts of hunger. This personal story introduces the focus of the book: the political economies of urban food provisioning in Istanbul. Feeding Istanbul chronologically discusses food provisioning in Istanbul from the 16th century to the present. Turkkan uses an impressive range of sources, including secondary historical materials, archival documents and collections, and ethno­graphic research, to suggest that Istanbul has experienced three food regimes, each with unique relationships between the central authority, economics, and food supplies. . . .

Mohamed El Asawy, Eman Badawy Ahmed

تسعى الدولة الي حوکمة العمران في مصر وذلک من خلال إصدار العديد من القوانين والتشريعات التخطيطية لرفع کفاءة التجمعات العمرانية، وتعتبر التعديلات المقترح تنفيذها على بنود قانون البناء الموحد من أهم التشريعات القانونية محل الدراسة في وقتنا الحالي. تتناول الدراسة تحليل وتقييم الأثر البيئي جراء تطبيق التعديلات المقترحة على متوسط الطاقة المستهلکة بالوحدات السکنية سواء بالسلب أو الإيجاب، مع ذکر خاص لمدى توافق تلک التعديلات مع التوصيات المقترحة بأکواد البناء المصري المعنية بالنواحي البيئية للمباني السکنية، بالاضافة الي بعض التعديلات المقترحة والتي يوصي البحث بضرورة ضمها الي قانون البناء الموحد. منهجية البحث: يتبع البحث المنهج الاستقرائي من خلال دراسة القوانين والمعايير الحاکمة لتصميم الوحدات السکنية والتي تشمل قانون البناء الموحد رقم 119 لسنة 2008 والضوابط والاشتراطات التخطيطية والبنائية للمدن المصرية 2020, والکود المصري لتحسين کفاءة استخدام الطاقة في المباني, بالاضافة الي الکود المصري للتهوية في المباني. ثم المنهج التطبقي وذلک من خلال اقتراح النموذج السکني للدراسة التطبيقية واستخدام برامج المحاکاة البيئية (designbuilder and energy plus) لقياس تاثير المتغيرات التصميمية المقترحة (ارتفاع المبنى والمسافات البينية بين المباني المتقابلة, والبروزات الخارجية, وطبقات الغلاف الخارجي المصمت, وأبعاد ونسب الفتحات الخارجية, والمناور السکنية الداخلية) علي استهلاک الطاقة بالمبني السکني. هذا وتشير نتائج الدراسة البحثية إلى أن تعديلات قانون البناء الموحد بمنظومة الاشتراطات الجديده2020 ذات تأثير ايجابي في زيادة الوفر في الطاقة المستهلکة للوحدات السکنية عن مثيلاتها في حال تطبيق قانون البناء الموحد لمقدار التوفير في الطاقة المستهلکة بمعدل 4% للمناور السکنية وبنسبة تتراوح ما بين 14 : 17% للبروزات ومن 12 : 16% لتأثير عرض الطريق وعلاقته بارتفاع المبني. Egypt seeks to govern urbanization by issuing many planning laws to increase the efficiency of urban communities. The proposed amendments to the Building Law are considered one of the most important legal studies during these days. The research focuses on analyzing and evaluating the environmental impact of applying amendments on the average energy consumption in residential buildings, whether negatively or positively. In addition to some proposed amendments, which the research recommends be included in the amendments. Research Methodology depends on the inductive approach by studying the laws for the housing unit’s design, which include the Building Law No. 119 of 2008, the planning and building requirements for Egyptian cities 2020, the Egyptian Code for Energy in Buildings, and the Egyptian code for ventilation in buildings. The second part depends on the applied approach by proposing the residential model for the applied study and using the environmental simulation programs (design builder and energy plus) to measure the effectiveness of the proposed design variables (building height, distances between opposite buildings, external shades, components of the building's external envelope, openings and courtyard) on the energy consumption of the residential building. The results of the study indicate that the modification of the building law with the new requirements (2020) has a positive effect on the building's energy saving compared to the case of applying the building law. The modifications achieve 4% in energy savings for the courtyard, 14:17 % for the cantilevers, and 12:16 % for the relationship between road width and the building height.

Alexander Wischnewski, Maximilian Geisslinger, Johannes Betz et al.

Motorsport has always been an enabler for technological advancement, and the same applies to the autonomous driving industry. The team TUM Auton-omous Motorsports will participate in the Indy Autonomous Challenge in Octo-ber 2021 to benchmark its self-driving software-stack by racing one out of ten autonomous Dallara AV-21 racecars at the Indianapolis Motor Speedway. The first part of this paper explains the reasons for entering an autonomous vehicle race from an academic perspective: It allows focusing on several edge cases en-countered by autonomous vehicles, such as challenging evasion maneuvers and unstructured scenarios. At the same time, it is inherently safe due to the motor-sport related track safety precautions. It is therefore an ideal testing ground for the development of autonomous driving algorithms capable of mastering the most challenging and rare situations. In addition, we provide insight into our soft-ware development workflow and present our Hardware-in-the-Loop simulation setup. It is capable of running simulations of up to eight autonomous vehicles in real time. The second part of the paper gives a high-level overview of the soft-ware architecture and covers our development priorities in building a high-per-formance autonomous racing software: maximum sensor detection range, relia-ble handling of multi-vehicle situations, as well as reliable motion control under uncertainty.

Zoia S. Podoba, Victor A. Gorshkov, Anastasiya A. Ozerova

By empirically examining the commodity structure of Japan's exports in 2000–2020, the authors have identified product groups with increased, diminished, newly emerged, and lost revealed comparative advantages (RCA). In 2020, Japan had RCA in 24 product groups with relatively high levels of product complexity and thus managed to maintain its highly diversified trade portfolio. However, increasing global competition poses potential risks to Japan's exports. Eight product groups with diminished and two product groups with lost RCA are signs of Japan's unsuccessful adaptation to the structural changes on the world markets. The newly emerged RCA, predominantly in the chemicals and allied industries, still mostly have lower index values in comparison to major trade partners, however, their contribution to Japan's exports is likely to expand. To enhance its comparative advantages, Japan should foster innovation which may positively affect national competitiveness but this depends on how the country will adapt to domestic and global challenges.

Emily Duncan

First paragraphs: Local is Our Future was published shortly before the rise of the COVID-19 pandemic, yet it makes a timely contribution critiquing economic globalization given the experiences of 2020. It emphasizes the need for shorter supply chains and champions local food systems by focusing on the structural forces that currently control the food system.  In the first three chapters, Norberg-Hodge explains and details the costs of economic globali­zation, which provides an adept introduction to understanding the structural impacts of financial deregulation on health, food security, environmen­tal consequences, and growing inequality. The fourth chapter covers a topic that might seem unlikely to be included in a book on local futures, as it describes the rise of extremism, yet this is a crucial analysis for current events. This book was published before the Black Lives Matter demon­strations that occurred around the world in sum­mer 2020; however, it provides a contextual backdrop for how the globalized financial system promotes economic insecurity that can lead to the adoption of a false narrative by the far right, as observed by the backlash to BIPOC (Black, Indigenous, and People of Color) communities demonstrating the need for increased equality. . . .

Michael Estrada, Sida Li, Xiangyu Cai

Through the method of Learning Feedback Linearization, we seek to learn a linearizing controller to simplify the process of controlling a car to race autonomously. A soft actor-critic approach is used to learn a decoupling matrix and drift vector that effectively correct for errors in a hand-designed linearizing controller. The result is an exactly linearizing controller that can be used to enable the well-developed theory of linear systems to design path planning and tracking schemes that are easy to implement and significantly less computationally demanding. To demonstrate the method of feedback linearization, it is first used to learn a simulated model whose exact structure is known, but varied from the initial controller, so as to introduce error. We further seek to apply this method to a system that introduces even more error in the form of a gym environment specifically designed for modeling the dynamics of car racing. To do so, we posit an extension to the method of learning feedback linearization; a neural network that is trained using supervised learning to convert the output of our linearizing controller to the required input for the racing environment. Our progress towards these goals is reported and the next steps in their accomplishment are discussed.