HELIN Digital Commons
Not a member yet
62477 research outputs found
Sort by
A Day in the Life: Luke Fonts Film
No full textProvidence College Department of Theatre, Dance & Film
John Bowab Studio Theatre
Student Film Festival 2025
Thursday, May 1, 2025, 7pm
Will Drew ‘25, A Day in the Life: Luke Fonts (3:49
Anti-feminism as a Forecasting Barometer for Political Radicalization: The Case of Bosnia and Herzegovina
No full textRight-wing and nationalist movements in disparate parts of the world have gathered significant strength in recent years. This dissertation investigates how anti-feminism and misogyny operate as sociocultural enablers of radicalization in Bosnia and Herzegovina, shaping both individual pathways to extremism and broader ideological movements. Situated at a critical juncture between European and Middle Eastern cultural influences, Bosnia and Herzegovina has long been a crossroads of cultures. Notably, Western Catholicism, Eastern Orthodoxy, Islam and, to a lesser extent, Judaism, all of which have established deep and historic cultural traditions. Each has also contributed significantly to the country’s entrenched patriarchal norms. The post-World War II establishment of what would become the Socialist Federal Republic of Yugoslavia attempted to enforce a break with these traditional, patriarchal gender roles with a series of highly progressive constitutions enshrining gender equality. This period of communist governance reflected economic growth and increased participation by women in the labor force while simultaneously suppressing religious practices. During the Yugoslav period, Bosnia and Herzegovina’s society began to reflect this attempt to reconfigure gender dynamics and gender roles. However, the collapse and disintegration of Yugoslavia in the 1990s and the subsequent 1992-1995 Bosnian War reversed many advances women made during the Yugoslav era as women faced not only a reversion to increased religiosity but also found themselves trapped between increasingly significant radical ethno-nationalist ideologies.
This dissertation investigates how Islamist and far-right ethno-nationalist groups in Bosnia and Herzegovina deploy anti-feminist rhetoric to justify political and social control. While both ideologies claim to protect traditional family structures, they do so in ways that reinforce male dominance and suppress gender equality. This study situates these narratives within Bosnia and Herzegovina’s post-war sociopolitical landscape, drawing on expert interviews and existing literature to analyze the implications of gender-based radicalization. This research explores the link between anti-feminist discourse and radicalization intrinsic in Bosnia and Herzegovina’s thoroughly polarized society using a range of qualitative methodologies to include a series of expert interviews
Paradoxical Pedagogy: Teaching Trauma-Informed Principles Within a System Built on Emotional Detachment
No full text
Human-Centered Advocacy: Requiring Trauma-Informed Lawyering Through Mandatory Continuing Legal Education
No full textLoad Analysis and Material Optimization for an Underwater Autonomy Sensorized Task Platform
No full textWith developing technology, options for fabrication and material selection broaden. An example is 3D printable photopolymer resin used to create parts serving several applications. An application of this photopolymer resin is the ONR research project for the creation of the sensorized task platform for a robot to use underwater. The resin in this project was used to fabricate custom-made connecting brackets. These fabricated parts were hastily designed with no detailed analysis on stress distributions or material consumption. Using SolidWorks simulation analysis and Instron machines for experimentation, the goal of this project was to modify the original part with a reduced weight of 10% from the original design with no increased risk of failure. From this requirement, several parts were modified in SolidWorks from the original model that consumed unnecessary material. After several studies were conducted for the models, the final model achieved a 22% to 24% material reduction with no compromise to its strength
Optimizing Indoor Localization Using RSSI and IQ Data with Machine Learning
No full textThis paper explores implementing and evaluating a Bluetooth Low Energy (BLE)-based indoor localization system using Received Signal Strength Indicator (RSSI) and Angle of Arrival (AoA) data via machine learning. A survey of localization technologies (RFID, GPS, ZigBee, and BLE) provides context on capabilities and limitations in indoor positioning. IQ data and phase-based angle estimation show how BLE 5.1’s direction-finding features enable sub-meter accuracy. A multi-phase experiment in a three-story academic building examines model performance with different tag distributions, movement patterns, and environmental constraints. Machine learning models such as Support Vector Machines and Deep Neural Networks are trained and evaluated across six phases. The best models achieve 85–92% accuracy in room-level localization despite real-world signal interference. Limitations such as generalizability and signal obstruction are additionally discussed. The study demonstrates the viability of BLE-based machine learning forscalable, semi-precise indoor localization and identifies areas for optimization and future work