Analyzing motion patterns in traffic videos can be exploited directly to generate highlevel descriptions of the video contents. Such descriptions may further be employed in different traffic applications such as traffic phase detection and abnormal event detection. One of the most recent and successful unsupervised methods for complex traffic scene analysis is based on topic models. In this paper, a two-level Sparse Topical Coding (STC) topic model is proposed to analyze traffic surveillance video sequences which contain hierarchical patterns with complicated motions and co-occurrences. The first level STC model is applied to automatically cluster optical flow features into motion patterns. Then, the second level STC model is used to cluster motion patterns into traffic phases. Experiments on a real world traffic dataset demonstrate the effectiveness of the proposed method against conventional onelevel topic model based methods. The results show that our two-level STC can successfully discover not only the lower level activities but also the higher level traffic phases, which makes a more appropriate interpretation of traffic scenes. Furthermore, based on the two-level structure, either activity anomalies or traffic phase anomalies can be detected, which cannot be achieved by the one-level structure.

In this study, we aim to use new deep-learning tools and convolutional neural networks for traffic analysis. ResNeXt architecture, one of the most potent architectures and has attracted much attention in various fields, has been proposed to examine the scene, and classify it into three categories: cars, bikes (bicycles/motorcycles), and pedestrians. Previous studies have focused more on one type of classification and reported only human-facial recognition or vehicle detection. In contrast, the proposed method uses precise architecture to perform the classification of three classes. The proposed plan has been implemented in several steps: the first stage is to divide the critical objects. In the next step, the characteristics of the obtained objects are extracted to classify the process into three classes. Experiments have been conducted on different and essential datasets such as high-traffic, low-quality, real-time scenes. Essential evaluation criteria such as accuracy, sensitivity, and specificity show that the performance of the proposed method has improved compared to the methods being compared. The accuracy criterion reached more than 92%, sensitivity about 89%, and specially to 90.25%. The proposed method can be used to implement intelligent cities, public safety, and metropolitan decisions and use the results in urban management, predictive modeling of lost data management, sequential data management, and generalizability.

In this paper, a trajectory learning-based vehicle tracking algorithm is presented which is a new top-down vehicle tracker. The history of trajectory is learnt by a novel sptiotemporal data base known center transition matrix, CTM. At first, the CTM is constructed on centers which are obtained using fuzzy clustering on vehicle trajectories. The i, j-th element of CTM indicates passing of the object from center i to center j in two consecutive frames which CTM is completed by multi-object tracking. The CTM is efficient in search of similar blobs in image sequences and can determine the radius and region of search and increasing of convergence rate of RLS predictor. The proposed tracking algorithm is tested in the intersection of a highway to a square which gives good results.

Dear Editor, In a visit to the Forensic Medicine Department of Ankara University, Turkey, some years ago, the authors of the letter noticed that the phrase "Olay Yeri Incelemesi" means "Event Scene Investigation" rather than "Crime Scene Investigation" is used in the country [1]. When we asked for the cause, the answer was convincing: "While investigating the scene, it is frequently observed that there was only one event or incident and no crime at all. So there is no need to endanger the mental health of citizens and society by misrepresenting like Westerners". As faculty members forensic medicine specialists, we did extensive searches on the Internet and academic databases (in English, Farsi, and Turkish), but we did not find a similar case in other countries. However, the response of our Turkish neighbors influenced our thinking and inevitably led the authors to write this letter. . .

Background and Objective:  The challenges present at various stages of crime scene investigation are among the most significant reasons for not achieving desirable results. Managers and experts in the field of crime scene investigation within the Criminal Investigation Department need to be aware of the existing challenges and the role each plays in the crime scene investigation process. Therefore, the aim of this research is to analyze the challenges facing the police in crime scene investigation and to provide appropriate solutions. Methodology:  This research is applied in terms of its objective and is developed with a qualitative (Delphi) approach. The data collection tools include document studies and in-depth interviews with the statistical population. The statistical population consists of the staff of the Tehran Criminal Investigation Department, with the Delphi panel comprising 44 crime scene investigation experts who have sufficient knowledge and experience in this field. They were selected using the snowball sampling method until theoretical saturation was achieved, and interviews were conducted with them in three stages. High agreement among respondents to the questions indicates the reliability of the research. Findings:  The challenges of crime scene investigation are categorized into two dimensions: 1. “Technical Dimension” and 2. “Managerial Dimension. ” The most important challenges include the lack of specialized and professional software, the crowding and congestion of unauthorized individuals, contamination and destruction of evidence, lack of strong coordination among different actors, absence of a cohesive and centralized management center, shortage of specialized equipment in forensic laboratories, weakness in public education, and weakness in the protection of the crime scene and evidence by first responders. Results:  Accurate initial assessment, sufficient training of investigating officers, use of advanced tools and equipment, comprehensive collection of evidence, and thorough protection of the crime scene play a significant role in reducing and addressing the challenges of crime scene investigation.

Computers might be used in crimes. They may also contain some evidences which prove a crime or be used in committing crimes. Therefore, these electronic equipments include valuable evidences for crime detection. In this article it is attempted to realize the importance of dealing with these kind of evidences without any major damage to them and how to answer the law enforcement officers in this regard.

Studying gunshot residue in determining suicide and homicide, weapon type, munitions, distance and angle of shooting is very helpful, because gunshot residue can be dissipated on hands, faces, clothes and nearby objects from holes of a trigger and weapon. When a gunshot is fired, the burned and semi-burned compositions are dissipated in the gas phase in all directions. The parameters used include: bullet, bullet casing, the semi-burned powder, which due to the function of the weapon, are dissipated around from the holster’ s holes in the form of gas and finally, the gunshot sound that can be heard by witnesses. Each of these elements can be helpful for the detection of a crime and criminal. Different instrumental methods can be used to collect gunshot residue and its analysis. Using sensors to investigate cases at a crime scene without the need for very expensive equipment, attracts attention. Recently applied reports concerning the use of sensors to analyze gunshot residue have been printed in various magazines which in this research will be studied. This research is intended to provide the stage to review and discuss gunshot residue and developed sensors to identify them.

The emergence of comparative literature bestowed to a great extent the democracy and justice to the world of doing research. One of its branches is interdisciplinary studies which deal with the mutual interactions among different sciences. Before the twentieth century, time was considered as one of the rigid criteria which was used to measure the world. By the advent of Einstein's theory of relativity, time was to be considered relatively. Despite classical authors who viewed time from the outside and considered it as the causal consequences, modern novelists distorted the time sequence and employed the stream of consciousness as a means of their narration. One of the most successful works, in this respect, is Faulkner's The Sound and the Fury (1929) in which he follows the theory of relativity and ignores the linear conception of time. The major concern in this paper is to analyze the impact of Einstein's relativity on the early twentieth novelist in general, and on The Sound and the Fury, in particular.

Background and Aim The purpose of this study is to investigate the position of traffic police in the management of road traffic accidents in the area of the Special Disciplinary Command in the west of Tehran province. Method The research method is quantitative in nature, applied in terms of purpose and descriptive-survey in terms of data collection method. The statistical population included managers and elites in the field of accidents. Using the Georgian and Morgan table, the population was limited to 180 people. In the present study, Pearson correlation coefficient was used to investigate the relationship between traffic police position and traffic accident management and to evaluate the level of traffic police coordination with relevant devices, a one-sample t-test was used. Findings The results of the research show that the main hypothesis and all three sub-hypotheses are confirmed. The obtained Pearson correlation coefficient is 0. 323, 0. 299, 0. 349 and 0. 311, respectively. Results A review of the decisions made confirms that less attention has been paid to the two priorities of traffic management and traffic accident prevention management. In ignoring the two categories of forecasting management and traffic accident prevention management, it is enough that the number of scientific resources in these two areas does not reach the number of fingers on both hands. Therefore, in order to reduce traffic losses in the coming years, the authorities should pay more attention to the two neglected clauses of traffic accident forecasting and prevention