Robust Data Association Using Fusion of Data-Driven and Engineered Features for Real-Time Pedestrian Tracking in Thermal Images

Object tracking is an essential problem in computer vision that has been extensively researched for decades. Tracking objects in thermal images is particularly difficult because of the lack of color information, low image resolution, or high similarity between objects of the same class. One of the main challenges in multi-object tracking, also referred to as the data association problem, is finding the correct correspondences between measurements and tracks and adapting the object appearance changes over time. We addressed this challenge of data association for thermal images by proposing three contributions. The first contribution consisted of the creation of a data-driven appearance score using five Siamese Networks, which operate on the image detection and on parts of it. Secondly, we engineered an original edge-based descriptor that improves the data association process. Lastly, we proposed a dataset consisting of pedestrian instances that were recorded in different scenarios and are used for training the Siamese Networks. The data-driven part of the data association score offers robustness, while feature engineering offers adaptability to unknown scenarios and their combination leads to a more powerful tracking solution. Our approach had a running time of 25 ms and achieved an average precision of 86.2% on publicly available benchmarks, containing real-world scenarios, as shown in the evaluation section.

An eight-state molecular sequential switch featuring a dual single-bond rotation photoreaction

Typical photowitches interconvert between two different states by simple isomerization reactions, which represents a fundamental limit for applications. To expand the switching capacity usually different photoswitches have to be linked together leading to strong increase in molecular weight, diminished switching function, and less precision and selectivity of switching events. Herein we present an approach for solving this essential problem with a different photoswitching concept. A basic molecular switch architecture provides precision photoswitching between eight different states via controlled rotations around three adjacent covalent bonds. All eight states can be populated one after another in an eight-step cycle by alternating between photochemical Hula-Twist isomerizations and thermal single bond rotations. By simply changing solvent and temperature the same switch can also undergo a different cycle instead interconverting just five isomers in a selective sequence. This behavior is enabled through the discovery of an unprecedented photoreaction, a one photon dual single bond rotation.

SERBIAN DIASPORABETWEEN DISSOLUTION AND UNITY

Cooperation between the Serbian diaspora and the Republic of Serbia is not expressed in full potential, because it is limited to a one-sided financial and partly cultural concept. In order for the Serbian diaspora to reach its full potential, it is necessary to expand the existing concepts. Contemporary problems in expression national identity require a more serious approach, because if only one member of the community is neglected, especially if he is in the diaspora, in the near future the consequences will be such that in addition to weakening awareness of belonging, the end result will be loss of national identity. This outcome can be prevented if the criteria of the current relationship between the Republic of Serbia and its citizens in the diaspora are redefined. Accent it is necessary to set on: (1) better and more comprehensive elements of statistical indicators of migration of domestic citizens; (2) a different approach to the economic draft budget of the Republic of Serbia, which would go beyond the current framework, short-term assistance from the diaspora in the form of remittances; 3) the issue of security of citizens of the Republic of Serbia is completely left to the states in which they currently exist, which is insufficient; (4) the cultural component is represented, but unfortunately through unilateral efforts mainly by the diaspora, while the home country is largely reserved. The essential problem is in the cooperation of these two sides of one state. If this cooperation remains at the level it is at now, the question is whether the sec-ond generation in the diaspora will have any empathy towards the country of their origin.

A proposed method for encrypting and sending confidential data using polynomials

With the improvements of cyberspace and communications, an essential problem was raised and that is how to secure the transmitted data and keep it confidential. Many techniques have been used for this purpose, some of them were broken but others were stayed immune against different attacks. Complexity of the used technique is one of the major reasons that kept it secure. To increase complexity, mathematics was used. In this paper, a method for encrypting and sending confidential data was proposed. The method depends on mathematical equations for encrypting data, sending and decrypting it. The method is complex, secure and workable.

Mathematical forecasting composition of secondary carbides in the single-crystal superalloys

Purpose: Predicting the specifics of the distribution of alloying elements between secondary carbides, their topology, and morphology, as well as the composition for a single-crystal multicomponent system of the type Ni-11.5Cr-5Co-3.6Al-4.5Ti-7W-0.8Mo-0.06C using the calculated CALPHAD (passive experiment) versus scanning electron microscopy (active experiment). Design/methodology/approach: This work presents the results of studies of the distribution of chemical elements in the composition of carbides, depending on their content in the system. The studies were carried out using an electron microscope with computer analysis of images and chemical composition. Findings: It was found that the influence of alloying elements on the composition of carbides is complex and is described by complex dependencies that correlate well with the obtained experimental results. Research limitations/implications: An essential problem is the prediction of the structure and properties of superalloys without or with a minimum number of experiments. Practical implications: The obtained dependencies can be used both for designing new superalloys and for improving the compositions of industrial alloys. Originality/value: The value of this work is that the obtained dependences of the influence of alloying elements on the dissolution (precipitation) temperatures and the distribution of elements in secondary carbides in the superalloy of the Ni-11.5Cr-5Co-3.6Al-4.5Ti-7W-0.8Mo-0.06C system. It was found that changes in the course of the curves of temperature dependence on the element content closely correlate with thermodynamic processes occurring in the system, that is, the curves exhibit extrema accompanying the change in the stoichiometry of carbides or the precipitation of new phases.

A proposed method for encrypting and sending confidential data using polynomials

With the improvements of cyberspace and communications, an essential problem was raised and that is how to secure the transmitted data and keep it confidential. Many techniques have been used for this purpose, some of them were broken but others were stayed immune against different attacks. Complexity of the used technique is one of the major reasons that kept it secure. To increase complexity, mathematics was used. In this paper, a method for encrypting and sending confidential data was proposed. The method depends on mathematical equations for encrypting data, sending and decrypting it. The method is complex, secure and workable.

JOKE, LAUGH AND CRY: QUALITATIVE ANALYSIS OF “MEME” IN PSYCHODYNAMICS AND COLLECTIVE PSYCHIATRIC CLINIC

Existing is a verb that encompasses basal biological categories - biochemical, cellular and molecular processes - and psychodynamics, these tied to the experiences of ones and the world. Mental health, then, has as essential problem the face of the other and the "Other" through limited mechanisms and, also, by affections marked by otherness. The question, therefore, was "the most viral memes are based on which psychic processes and, therefore, what was the related otherness?". Three accounts on Instagram - @jedinizm, @pacifylyrics and @mariamchami - were evaluated qualitatively based on the parameters (i) communication objective, (ii) particular psychic function made collective and (iii) taboos and restrictive social norms addressed; clash arose by the critical reading of Sigmund Freud and Maria Homem. The joke was observed in the three accounts, @pacifylyrics presented greater conjugation between images - individual memes - and songs, @mariamchami, in turn, acts in a disruptive way, demystifying the image of the muslim woman through the ridicule of the intolerant thinking of the viewer. @jedinizm, more attentive to the public in general, brings themes such as adultery and financial bankruptcy as objects of laughter and subversion. In all cases, the meme acted as elaboration of affections for conscious denial, raising the characteristic austerity of forbidden themes in the social norm. It is, in fact, a category of popular education in collective mental health.

Analytical Study of Task Offloading Techniques using Deep Learning

The Internet of Things (IoT) systems create a large amount of sensing information. The consistency of this information is an essential problem for ensuring the quality of IoT services. The IoT data, however, generally suffers due to a variety of factors such as collisions, unstable network communication, noise, manual system closure, incomplete values and equipment failure. Due to excessive latency, bandwidth limitations, and high communication costs, transferring all IoT data to the cloud to solve the missing data problem may have a detrimental impact on network performance and service quality. As a result, the issue of missing information should be addressed as soon as feasible by offloading duties like data prediction or estimations closer to the source. As a result, the issue of incomplete information must be addressed as soon as feasible by offloading duties such as predictions or assessment to the network’s edge devices. In this work, we show how deep learning may be used to offload tasks in IoT applications.

Hybrid-Quantum approach for the optimal lockdown to stop the SARS-CoV-2 community spread subject to maximizing nation economy globally

Owing to the SARS-CoV-2 epidemic (severe acute respiratory coronavirus 2 syndromes), the global situation has changed drastically. Several countries, including India, Europe, U.S.A., introduced a full state/nation lockdown to minimize the disease transmission through human interaction after the virus entered the population and to minimize the loss of human life. Millions of people have gone unemployed due to lockdown implementation, resulting in business and industry closure and leading to a national economic slowdown. Therefore, preventing the spread of the COVID-19 virus in the world while also preserving the global economy is an essential problem requiring an effective and immediate solution. Using the compartmental epidemiology S, E, I, R or D (Susceptible, Exposed, Infectious, Recovery or Death) model extended to multiple population regions we predict the evolution of the SARS-CoV-2 disease and construct an optimally scheduled lockdown calendar to execute lockdown over phases, using the well-known Knapsack problem. A comparative analysis of both classical and quantum models shows that our model decreases SARS-CoV-2 active cases while retaining the average global economic factor, GDP, in contrast to the scenario with no lockdown.