Violence in the Medieval Church before the First Crusade

The attitude of the medieval church towards violence before the First Crusade in 1095 underwent a significant institutional evolution, from the peaceful tradition of the New Testament and the Roman persecution, through the prelate-led military campaigns of the Carolingian period and the Peace of God era. It would be superficially easy to characterize this transformation as the pragmatic and entirely secular response of a growing power to the changing world. However, such a simplification does not fully do justice to the underlying theology. While church leaders from the 5th Century to the 11th had vastly different motivations and circumstances under which to develop their responses to a variety of violent activities, the teachings of Augustine of Hippo provided a unifying theme. Augustine’s just war theology, in establishing which conflicts are acceptable in the eyes of God, focused on determining whether a proper causa belli or basis for war exists, and then whether a legitimate authority declares and leads the war. Augustine masterfully integrated aspects of the Old and New Testaments to create a lasting and compelling case for his definition of justified violence. Although at different times and places his theology has been used to support a variety of different attitudes, the profound influence of his work on the medieval church’s evolving position on violence is clear.

Lethal Interpersonal Violence in the Middle Pleistocene

Evidence of interpersonal violence has been documented previously in Pleistocene members of the genus Homo, but only very rarely has this been posited as the possible manner of death. Here we report the earliest evidence of lethal interpersonal violence in the hominin fossil record. Cranium 17 recovered from the Sima de los Huesos Middle Pleistocene site shows two clear perimortem depression fractures on the frontal bone, interpreted as being produced by two episodes of localized blunt force trauma. The type of injuries, their location, the strong similarity of the fractures in shape and size, and the different orientations and implied trajectories of the two fractures suggest they were produced with the same object in face-to-face interpersonal conflict. Given that either of the two traumatic events was likely lethal, the presence of multiple blows implies an intention to kill. This finding shows that the lethal interpersonal violence is an ancient human behavior and has important implications for the accumulation of bodies at the site, supporting an anthropic origin.

Detection of Construction Workers in Video Frames for Automatic Initialization of Vision Trackers

Vision based tracking can provide the spatial location of construction entities such as equipment, workers, and materials in large scale, congested construction sites. It tracks entities in video streams by inferring their locations based on the entities’ visual features and motion histories. To initiate the process, it is necessary to determine the pixel areas corresponding to the construction entities to be tracked in the following consecutive video frames. In order to fully automate the process, an automated way of initialization is needed. This paper presents the method for construction worker detection which can automatically recognize and localize construction workers in video frames. The method first finds the foreground areas of moving objects using a background subtraction method. Within these foreground areas, construction workers are recognized based on the histogram of oriented gradients (HOG) and histogram of the HSV colors. HOG’s have proved to work effectively for detection of people, and the histogram of HSV colors helps differentiate between pedestrians and construction workers wearing safety vests. Preliminary experiments show that the proposed method has the potential to automate the initialization process of vision based tracking.

Enhancement of Construction Equipment Detection in Video Frames by Combining with Tracking

Vision-based object detection has been introduced in construction for recognizing and locating construction entities in on-site camera views. It can provide spatial locations of a large number of entities, which is beneficial in large-scale, congested construction sites. However, even a few false detections prevent its practical applications. In resolving this issue, this paper presents a novel hybrid method for locating construction equipment that fuses the function of detection and tracking algorithms. This method detects construction equipment in the video view by taking advantage of entities' motion, shape, and color distribution. Background subtraction, Haar-like features, and eigen-images are used for motion, shape, and color information, respectively. A tracking algorithm steps in the process to make up for the false detections. False detections are identified by catching drastic changes in object size and appearance. The identified false detections are replaced with tracking results. Preliminary experiments show that the combination with tracking has the potential to enhance the detection performance.

Construction Worker Detection in Video Frames for Initializing Vision Trackers

Monitoring the location of resources on large scale, congested, outdoor sites can be performed more efficiently with vision tracking, as this approach does not require any pre-tagging of resources. However, the greatest impediment to the use of vision tracking in this case is the lack of detection methods that are needed to automatically mark the resources of interest and initiate the tracking. This paper presents such a novel method for construction worker detection that localizes construction workers in video frames. The proposed method exploits motion, shape, and color cues to narrow down the detection regions to moving objects, people, and finally construction workers, respectively. The three cues are characterized by using background subtraction, the histogram of oriented gradients (HOG), and the HSV color histogram. The method has been tested on videos taken in various environments. The results demonstrate its suitability for automatic initialization of vision trackers.

Biologically Inspired Features for Scene Classification in Video Surveillance

Inspired by human visual cognition mechanism, this paper first presents a scene classification method based on an improved standard model feature. Compared with state-of-the-art efforts in scene classification, the newly proposed method is more robust, more selective, and of lower complexity. These advantages are demonstrated by two sets of experiments on both our own database and standard public ones. Furthermore, occlusion and disorder problems in scene classification in video surveillance are also first studied in this paper.

Extraction and Clustering of Motion Trajectories in Video

A system is described that tracks moving objects in a video dataset so as to extract a representation of the objects' 3D trajectories. The system then finds hierarchical clusters of similar trajectories in the video dataset. Objects' motion trajectories are extracted via an EKF formulation that provides each object's 3D trajectory up to a constant factor. To increase accuracy when occlusions occur, multiple tracking hypotheses are followed. For trajectory-based clustering and retrieval, a modified version of edit distance, called longest common subsequence (LCSS) is employed. Similarities are computed between projections of trajectories on coordinate axes. Trajectories are grouped based, using an agglomerative clustering algorithm. To check the validity of the approach, experiments using real data were performed.

Automatic 2D Hand Tracking in Video Sequences

In gesture and sign language video sequences, hand motion tends to be rapid, and hands frequently appear in front of each other or in front of the face. Thus, hand location is often ambiguous, and naive color-based hand tracking is insufficient. To improve tracking accuracy, some methods employ a prediction-update framework, but such methods require careful initialization of model parameters, and tend to drift and lose track in extended sequences. In this paper, a temporal filtering framework for hand tracking is proposed that can initialize and reset itself without human intervention. In each frame, simple features like color and motion residue are exploited to identify multiple candidate hand locations. The temporal filter then uses the Viterbi algorithm to select among the candidates from frame to frame. The resulting tracking system can automatically identify video trajectories of unambiguous hand motion, and detect frames where tracking becomes ambiguous because of occlusions or overlaps. Experiments on video sequences of several hundred frames in duration demonstrate the system's ability to track hands robustly, to detect and handle tracking ambiguities, and to extract the trajectories of unambiguous hand motion.

Optimal Scheduling of Secondary Content for Aggregation in Video-on-Demand Systems

Dynamic service aggregation techniques can exploit skewed access popularity patterns to reduce the costs of building interactive VoD systems. These schemes seek to cluster and merge users into single streams by bridging the temporal skew between them, thus improving server and network utilization. Rate adaptation and secondary content insertion are two such schemes. In this paper, we present and evaluate an optimal scheduling algorithm for inserting secondary content in this scenario. The algorithm runs in polynomial time, and is optimal with respect to the total bandwidth usage over the merging interval. We present constraints on content insertion which make the overall QoS of the delivered stream acceptable, and show how our algorithm can satisfy these constraints. We report simulation results which quantify the excellent gains due to content insertion. We discuss dynamic scenarios with user arrivals and interactions, and show that content insertion reduces the channel bandwidth requirement to almost half. We also discuss differentiated service techniques, such as N-VoD and premium no-advertisement service, and show how our algorithm can support these as well.

Civil Rights on the Cell Block: Race, Reform, and Violence in Texas Prisons and the Nation, 1945-1990

This study, "Civil Rights on the Cell Block: Race, Reform, and Violence in Texas Prisons and the Nation, 1945-1990," offers a new perspective on the historical origins of the modern prison industrial complex, sexual violence in working-class culture, and the ways in which race shaped the prison experience. This study joins new scholarship that reperiodizes the Civil Rights era while also considering how violence and radicalism shaped the civil rights struggle. It places the criminal justice system at the heart of both an older racial order and within a prison-made civil rights movement that confronted the prison's power to deny citizenship and enforce racial hierarchies. By charting the trajectory of the civil rights movement in Texas prisons, my dissertation demonstrates how the internal struggle over rehabilitation and punishment shaped civil rights, racial formation, and the political contest between liberalism and conservatism. This dissertation offers a close case study of Texas, where the state prison system emerged as a national model for penal management. The dissertation begins with a hopeful story of reform marked by an apparently successful effort by the State of Texas to replace its notorious 1940s plantation/prison farm system with an efficient, business-oriented agricultural enterprise system. When this new system was fully operational in the 1960s, Texas garnered plaudits as a pioneering, modern, efficient, and business oriented Sun Belt state. But this reputation of competence and efficiency obfuscated the reality of a brutal system of internal prison management in which inmates acted as guards, employing coercive means to maintain control over the prisoner population. The inmates whom the prison system placed in charge also ran an internal prison economy in which money, food, human beings, reputations, favors, and sex all became commodities to be bought and sold. I analyze both how the Texas prison system managed to maintain its high external reputation for so long in the face of the internal reality and how that reputation collapsed when inmates, inspired by the Civil Rights Movement, revolted. My dissertation shows that this inmate Civil Rights rebellion was a success in forcing an end to the existing system but a failure in its attempts to make conditions in Texas prisons more humane. The new Texas prison regime, I conclude, utilized paramilitary practices, privatized prisons, and gang-related warfare to establish a new system that focused much more on law and order in the prisons than on the legal and human rights of prisoners. Placing the inmates and their struggle at the heart of the national debate over rights and "law and order" politics reveals an inter-racial social justice movement that asked the courts to reconsider how the state punished those who committed a crime while also reminding the public of the inmates' humanity and their constitutional rights.

Performance assessment in serious games: Compensating for the effects of randomness

This paper is about performance assessment in serious games. We conceive serious gaming as a process of player-lead decision taking. Starting from combinatorics and item-response theory we provide an analytical model that makes explicit to what extent observed player performances (decisions) are blurred by chance processes (guessing behaviors). We found large effects both theoretically and practically. In two existing serious games random guess scores were found to explain up to 41% of total scores. Monte Carlo simulation of random game play confirmed the substantial impact of randomness on performance. For valid performance assessments, be it in-game or post-game, the effects of randomness should be included to produce re-calibrated scores that can reasonably be interpreted as the players´ achievements.