nils-herrmann/clean_scirepeval huggingface dataset:
Efficiency and Security of Data with Symmetric Encryption Algorithms

In this paper, we proposed the encryption algorithm to encrypt plaintext to cipher text and the decryption algorithm to do the reverse. We applied the basic computing operations to design these algorithms in this study. We used the inserting dummy symbols, rotating, transposition, shifting, complement and inserting control byte to build the data and tables in the encryption algorithm. These operations are simple and easily to implement. Without knowing the data and tables of encryption, it is difficult to do cryptanalysis. In the decryption algorithm, we used these data and tables to decrypt cipher text to plaintext. We can easily apply these algorithms to transmit data in network and the data transmission is secure.  Encryption; Decryption; Data transmission; Cipher text; Plaintext; Encryption
Moving object detection, tracking and classification for smart video surveillance

MOVING OBJECT DETECTION, TRACKING AND CLASSIFICATION FOR SMART VIDEO SURVEILLANCE Yiğithan Dedeoğlu M.S. in Computer Engineering Supervisor: Assist. Prof. Dr. Uğur Güdükbay August, 2004 Video surveillance has long been in use to monitor security sensitive areas such as banks, department stores, highways, crowded public places and borders. The advance in computing power, availability of large-capacity storage devices and high speed network infrastructure paved the way for cheaper, multi sensor video surveillance systems. Traditionally, the video outputs are processed online by human operators and are usually saved to tapes for later use only after a forensic event. The increase in the number of cameras in ordinary surveillance systems overloaded both the human operators and the storage devices with high volumes of data and made it infeasible to ensure proper monitoring of sensitive areas for long times. In order to filter out redundant information generated by an array of cameras, and increase the response time to forensic events, assisting the human operators with identification of important events in video by the use of “smart” video surveillance systems has become a critical requirement. The making of video surveillance systems “smart” requires fast, reliable and robust algorithms for moving object detection, classification, tracking and activity analysis. In this thesis, a smart visual surveillance system with real-time moving object detection, classification and tracking capabilities is presented. The system operates on both color and gray scale video imagery from a stationary camera. It can handle object detection in indoor and outdoor environments and under changing illumination conditions. The classification algorithm makes use of the shape of the detected objects and temporal tracking results to successfully categorize objects into pre-defined classes like human, human group and vehicle. The system is also able to detect the natural phenomenon fire in various scenes reliably. The proposed tracking algorithm successfully tracks video objects even in full occlusion cases. In addition to these, some important needs of a robust iii
Two-stream RNN/CNN for action recognition in 3D videos

The recognition of actions from video sequences has many applications in health monitoring, assisted living, surveillance, and smart homes. Despite advances in sensing, in particular related to 3D video, the methodologies to process the data are still subject to research. We demonstrate superior results by a system which combines recurrent neural networks with convolutional neural networks in a voting approach. The gated-recurrent-unit-based neural networks are particularly well-suited to distinguish actions based on long-term information from optical tracking data; the 3D-CNNs focus more on detailed, recent information from video data. The resulting features are merged in an SVM which then classifies the movement. In this architecture, our method improves recognition rates of state-of-the-art methods by 14% on standard data sets.
Quality of life in the anxiety disorders: a meta-analytic review.

There has been significant interest in the impact of anxiety disorders on quality of life. In this meta-analytic review, we empirically evaluate differences in quality of life between patients with anxiety disorders and nonclinical controls. Thirty-two patient samples from 23 separate studies (N=2892) were included in the analysis. The results yielded a large effect size indicating poorer quality of life among anxiety disorder patients vs. controls and this effect was observed across all anxiety disorders. Compared to control samples, no anxiety disorder diagnosis was associated with significantly poorer overall quality of life than was any other anxiety disorder diagnosis. Examination of specific domains of QOL suggests that impairments may be particularly prominent among patients with post-traumatic stress disorder. QOL domains of mental health and social functioning were associated with the highest levels of impairment among anxiety disorder patients. These findings are discussed in the context of future research on the assessment of quality of life in the anxiety disorders.
Adaptive comanagement for building resilience in social-ecological systems.

Ecosystems are complex adaptive systems that require flexible governance with the ability to respond to environmental feedback. We present, through examples from Sweden and Canada, the development of adaptive comanagement systems, showing how local groups self-organize, learn, and actively adapt to and shape change with social networks that connect institutions and organizations across levels and scales and that facilitate information flows. The development took place through a sequence of responses to environmental events that widened the scope of local management from a particular issue or resource to a broad set of issues related to ecosystem processes across scales and from individual actors, to group of actors to multiple-actor processes. The results suggest that the institutional and organizational landscapes should be approached as carefully as the ecological in order to clarify features that contribute to the resilience of social-ecological systems. These include the following: vision, leadership, and trust; enabling legislation that creates social space for ecosystem management; funds for responding to environmental change and for remedial action; capacity for monitoring and responding to environmental feedback; information flow through social networks; the combination of various sources of information and knowledge; and sense-making and arenas of collaborative learning for ecosystem management. We propose that the self-organizing process of adaptive comanagement development, facilitated by rules and incentives of higher levels, has the potential to expand desirable stability domains of a region and make social-ecological systems more robust to change.
Knowledge Management: An Introduction and Perspective

In the mid-1980s, individuals and organizations began to appreciate the increasingly important role of knowledge in the emerging competitive environment. International competition was changing to increasingly emphasize product and service quality, responsiveness, diversity and customization. Some organizations, such as USbased Chaparral Steel, had been pursuing a knowledge focus for some years, but during this period it started to become a more wide-spread business concern. These notions appeared in many places throughout the world – almost simultaneously in the way bubbles appear in a kettle of superheated water! Over a brief period from 1986 to 1989, numerous reports appeared in the public domain concerning how to manage knowledge explicitly. There were studies, results of corporate efforts, and conferences on the topic.
2D diffuse optical imaging using clustered sparsity

Diffuse optical imaging (DOI) is a non-invasive technique which measures hemodynamic changes in the tissue with near infrared light, and has been increasingly used to study brain functions. Due to the nature of light propagation in the tissue, the reconstruction problem is severely ill-posed. Sparsity-regularization has achieved promising results in recent works for linearized DOI problem. In this paper, we exploit more prior information to improve DOI besides sparsity. Based on the functional specialization of the brain, the in vivo absorption changes caused by specific brain function can be clustered in certain region(s) and not randomly distributed. Thus, a new algorithm is proposed to utilize this prior in reconstruction. Results of numerical simulations and phantom experiments have demonstrated the superiority of the proposed method over the state-of-the-art.
Youth texting: Help or hindrance to literacy?

An extensive amount of research has been performed in recent years into the widespread practice of text messaging in youth. As part of this broad area of research, the associations between youth texting and literacy have been investigated in a variety of contexts. A comprehensive, semi-systematic review of the literature into texting and literacy was conducted, with a particular focus on quantitative empirical studies. Media reports, teacher surveys, and qualitative studies were also taken into consideration as part of this wide-ranging examination of previous research into this phenomenon. There were no clear positive or negative links discovered between adolescent texting practices and literacy, with the research findings in this study area best summarized as mixed and inconclusive. More studies in this research area are required, especially of an experimental or longitudinal kind. In addressing the debate on the impact of texting on literacy, research analyses as well as media reports would benefit from a more balanced presentation of existing findings.
The emotion probe. Studies of motivation and attention.

Emotions are action dispositions--states of vigilant readiness that vary widely in reported affect, physiology, and behavior. They are driven, however, by only 2 opponent motivational systems, appetitive and aversive--subcortical circuits that mediate reactions to primary reinforcers. Using a large emotional picture library, reliable affective psychophysiologies are shown, defined by the judged valence (appetitive/pleasant or aversive/unpleasant) and arousal of picture percepts. Picture-evoked affects also modulate responses to independently presented startle probe stimuli. In other words, they potentiate startle reflexes during unpleasant pictures and inhibit them during pleasant pictures, and both effects are augmented by high picture arousal. Implications are elucidated for research in basic emotions, psychopathology, and theories of orienting and defense. Conclusions highlight both the approach's constraints and promising paths for future study.
An Empirical Analysis of the Influence of Fault Space on Search-Based Automated Program Repair

Automated program repair (APR) has attracted great research attention, and various techniques have been proposed. Search-based APR is one of the most important categories among these techniques. Existing researches focus on the design of effective mutation operators and searching algorithms to better find the correct patch. Despite various efforts, the effectiveness of these techniques are still limited by the search space explosion problem. One of the key factors attribute to this problem is the quality of fault spaces as reported by existing studies. This motivates us to study the importance of the fault space to the success of finding a correct patch. Our empirical study aims to answer three questions. Does the fault space significantly correlate with the performance of search-based APR? If so, are there any indicative measurements to approximate the accuracy of the fault space before applying expensive APR techniques? Are there any automatic methods that can improve the accuracy of the fault space? We observe that the accuracy of the fault space affects the effectiveness and efficiency of search-based APR techniques, e.g., the failure rate of GenProg could be as high as 60% when the real fix location is ranked lower than 10 even though the correct patch is in the search space. Besides, GenProg is able to find more correct patches and with fewer trials when given a fault space with a higher accuracy. We also find that the negative mutation coverage, which is designed in this study to measure the capability of a test suite to kill the mutants created on the statements executed by failing tests, is the most indicative measurement to estimate the efficiency of search-based APR. Finally, we confirm that automated generated test cases can help improve the accuracy of fault spaces, and further improve the performance of search-based APR techniques. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org.
Microservice Ambients: An Architectural Meta-Modelling Approach for Microservice Granularity

Isolating fine-grained business functionalities byboundaries into entities called microservices is a core activityunderlying microservitization. We define microservitization asthe paradigm shift towards microservices. Determining theoptimal microservice boundaries (i.e. microservice granularity) is among the key microservitization design decisions thatinfluence the Quality of Service (QoS) of the microservice applicationat runtime. In this paper, we provide an architecturecentricapproach to model this decision problem. We build onambients — a modelling approach that can explicitly capturefunctional boundaries and their adaptation. We extend the aspect-oriented architectural meta-modelling approach of ambients—AMBIENT-PRISMA — with microservice ambients. A microservice ambient is a modelling concept that treatsmicroservice boundaries as an adaptable first-class entity. Weuse a hypothetical online movie subscription-based systemto capture a microservitization scenario using our aspectorientedmodelling approach. The results show the ability ofmicroservice ambients to express the functional boundary of amicroservice, the concerns of each boundary, the relationshipsacross boundaries and the adaptations of these boundaries. Additionally, we evaluate the expressiveness and effectivenessof microservice ambients using criteria from ArchitectureDescription Language (ADL) classification frameworkssince microservice ambients essentially support architecturedescription for microservices. The evaluation focuses on thefundamental modelling constructs of microservice ambientsand how they support microservitization properties such asutility-driven design, tool heterogeneity and decentralised governance. The evaluation highlights how microservice ambientssupport analysis, evolution and mobility/location awarenesswhich are significant to quality-driven microservice granularityadaptation. The evaluation is general and irrespective of theparticular application domain and the business competenciesin that domain.
Internet Scale User-Generated Live Video Streaming: The Twitch Case

Twitch is a live video streaming platform used for broadcasting video gameplay, ranging from amateur players to eSports tournaments. This platform has gathered a substantial world wide community, reaching more than 1.7 million broadcasters and 100 million visitors every month. Twitch is fundamentally different from “static” content distribution platforms such as YouTube and Netflix, as streams are generated and consumed in real time. In this paper, we explore the Twitch infrastructure to understand how it manages live streaming delivery to an Internet-wide audience. We found Twitch manages a geo-distributed infrastructure, with presence in four continents. Our findings show that Twitch dynamically allocates servers to channels depending on their popularity. Additionally, we explore the redirection strategy of clients to servers depending on their region and the specific channel.
Fast Cryptographic Computation on Intel ® Architecture Processors Via Function Stitching

Cryptographic applications often run more than one independent algorithm such as encryption and authentication. This fact provides a high level of parallelism which can be exploited by software and converted into instruction level parallelism to improve overall performance on modern super-scalar processors. We present fast and efficient methods of computing such pairs of functions on IA processors using a method called " function stitching ". Instead of computing pairs of functions sequentially as is done today in applications/libraries, we replace the function calls by a single call to a composite function that implements both algorithms. The execution time of this composite function can be made significantly shorter than the sums of the execution times for the individual functions and, in many cases, close to the execution time of the slower function. Function stitching is best done at a very fine grain, interleaving the code for the individual algorithms at an instruction-level granularity. This results in excellent utilization of the execution resources in the processor core with a single thread. We show how stitching pairs of functions together in a fine-grained manner results in excellent performance on IA processors. Currently, applications perform the functions sequentially. We demonstrate performance gains of 1.4X-1.9X with stitching over the best sequential function performance. We show performance results achieved by this method on the Intel ® processors based on the Westmere architecture.
INTELLIGENT WHEELCHAIR FOR PEOPLE WITH DISABILITIES

People make use of different languages to express their thoughts in a different way. But, it is difficult for the people who are affected by paralysis and stroke. Hence, there is a need to develop a platform for those people who are physically challengeable. An Embedded device shall address the above said problems. Based on the ARM processor the operation takes place. The device is designed with an intelligent wheelchair and the People With Disabilities (PWD) can direct it. By pressing the keypad (buttons) in the device, people with disabilities can move the wheelchair. In this process, the line following algorithm is implemented. To direct the wheelchair, L298 motor driver is used with the help of an ultrasonic obstacle sensor. By pressing a button, an automatic call to the doctor takes place if the PWD needs critical help. The GSM modem is used to forward the call. The LCD shows the basic needs of PWD which is already assigned in the buttons. On pressing the button, a text is displayed in the LCD with a buzzer sound. This device provides a unique mobility for the people with disabilities.
Parametric Optimization for Practical Control Systems Design

In this contribution, calculation machinery and code to compute different performance indices, which are necessary for the parametric optimization, are proposed. Moreover, a short review about parametric optimization is carried out. It is highlighted that normally only the ISE (Integral Square Error) performance index is used for control system design. One reason for that is the existence of several numerical algorithms to compute it along the infinite trajectory at once. Finally, an optimal design of a PI controller is used to illustrate and compare the new algorithms.
Enterprise agility and the enabling role of information technology

18 May 2005  19 June 2005  9 January 2006  In turbulent environments, enterprise agility, that is, the ability of firms to sense environmental change and respond readily, is an important determinant of firm success. We define and deconstruct enterprise agility, delineate enterprise agility from similar concepts in the business research literature, explore the underlying capabilities that support enterprise agility, explicate the enabling role of information technology (IT) and digital options, and propose a method for measuring enterprise agility. The concepts in this paper are offered as foundational building blocks for the overall research program on enterprise agility and the enabling role of IT.  (2006) 15, 120–131. doi:10.1057/palgrave.ejis.3000600
Generating Haptic Textures with a Vibrotactile Actuator

Vibrotactile actuation is mainly used to deliver buzzing sensations. But if vibrotactile actuation is tightly coupled to users' actions, it can be used to create much richer haptic experiences. It is not well understood, however, how this coupling should be done or which vibrotactile parameters create which experiences. To investigate how actuation parameters relate to haptic experiences, we built a physical slider with minimal native friction, a vibrotactile actuator and an integrated position sensor. By vibrating the slider as it is moved, we create an experience of texture between the sliding element and its track. We conducted a magnitude estimation experiment to map how granularity, amplitude and timbre relate to the experiences of roughness, adhesiveness, sharpness and bumpiness. We found that amplitude influences the strength of the perceived texture, while variations in granularity and timbre create distinct experiences. Our study underlines the importance of action in haptic perception and suggests strategies for deploying such tightly coupled feedback in everyday devices.
Searching for the elusive gift: advances in talent identification in sport.

The incentives for sport organizations to identify talented athletes from a young age continue to grow, yet effective talent identification remains a challenging task. This opinion paper examines recent advances in talent identification, focusing in particular on the emergence of new approaches that may offer promise to identify talent (e.g., small-sided games, genetic testing, and advanced statistical analyses). We appraise new multi-disciplinary and large-scale population studies of talent identification, provide a consideration of the most recent psychological predictors of performance, examine the emergence of new approaches that strive to diminish biases in talent identification, and look at the rise in interest in talent identification in Paralympic sport.
The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS): A dynamic, multimodal set of facial and vocal expressions in North American English

The RAVDESS is a validated multimodal database of emotional speech and song. The database is gender balanced consisting of 24 professional actors, vocalizing lexically-matched statements in a neutral North American accent. Speech includes calm, happy, sad, angry, fearful, surprise, and disgust expressions, and song contains calm, happy, sad, angry, and fearful emotions. Each expression is produced at two levels of emotional intensity, with an additional neutral expression. All conditions are available in face-and-voice, face-only, and voice-only formats. The set of 7356 recordings were each rated 10 times on emotional validity, intensity, and genuineness. Ratings were provided by 247 individuals who were characteristic of untrained research participants from North America. A further set of 72 participants provided test-retest data. High levels of emotional validity and test-retest intrarater reliability were reported. Corrected accuracy and composite "goodness" measures are presented to assist researchers in the selection of stimuli. All recordings are made freely available under a Creative Commons license and can be downloaded at https://doi.org/10.5281/zenodo.1188976.