nils-herrmann/clean_scirepeval huggingface dataset:
Dimensions of Cyber-Attacks: Cultural, Social, Economic, and Political

Essential systems providing water, electricity, healthcare, finance, food, and transportation are now increasingly software dependent, distributed, and interconnected. The detrimental consequences of this growing dependence become apparent during times of political conflict, social instability, and other traumatic events. The Internet has made information exchange easier and more efficient, but it has also created a new space in which criminals and terrorists can operate almost undetected. No longer is modern human conflict confined to the physical world; it has spread to cyberspace. Cyberspace is a massive socio technical system of systems, with a significant component being the humans involved. Current anomaly detection models focus primarily on analyzing network traffic to prevent malicious activities, but it has been shown that such approaches fail to account for human behaviors behind the anomalies. Evidence is growing that more cyber-attacks are associated with social, political, economic, and cultural (SPEC) conflicts. It is also now known that cyber-attackers' level of socio-technological sophistication, their backgrounds, and their motivations, are essential components to predicting, preventing, and tracing cyber-attacks. Thus, SPEC factors have the potential to be early predictors for outbreaks of anomalous activities, hostile attacks, and other security breaches in cyberspace.
How Personal Experience and Technical Knowledge Affect Using Conversational Agents

Conversational agents (CA) use dialogues to interact with users so as to offer an experience of naturalistic interaction. However, due to the low transparency and poor explanability of mechanism inside CA, individual's understanding of CA's capabilities may affect how the individual interacts with CA and the sustainability of CA use. To examine how users' understanding affect perceptions and experiences of using CA, we conducted a laboratory study asking 41 participants performed a set of tasks using Apple Siri. We independently manipulated two factors: (1) personal experience of using CA, and (2) technical knowledge about CA's system model. We conducted mixed-method analyses of post-task usability measures and interviews, and confirmed that use experience and technical knowledge affects perceived usability and mental models differently.
Relationship between the quality of children's handwriting and the Beery Buktenica developmental test of visuomotor integration after one year of writing tuition.

We examined whether the three subtests of the Beery Buktenica developmental test of visuomotor integration predicted quality of handwriting across and within groups of boys and girls classified as proficient, at risk or non-proficient writers according to the Concise Assessment Scale for Children's Handwriting.



The Beery Buktenica developmental test of visuomotor integration and the Concise Assessment Scale for Children's Handwriting tests were administered to 240 grade 2 children.



Proficient writers scored better on the visuomotor integration subtest than non-proficient writers, while proficient and at risk writers scored better than non-proficient writers on the motor coordination subtest. No differences were found on the visual perception subtest. Girls were more often classified as proficient writers than boys, and they scored better on the motor coordination subtest. Across groups, regression indicated that gender and both the visuomotor integration subtest and the motor coordination subtest were significant predictors for the quality of handwriting (i.e., accounted for 17% of the variance).



After one year of writing tuition, the visuomotor integration subtest (and to a lesser extent the motor coordination subtest) but not the visual perception subtest significant relates to quality of children's handwriting as measured with the Concise Assessment Scale for Children's Handwriting. However, the relatively little variance explained also points to other abilities and/or task constraints that underlie quality of handwriting.
Steerable CNNs

It has long been recognized that the invariance and equivariance properties of a representation are critically important for success in many vision tasks. In this paper we present Steerable Convolutional Neural Networks, an efficient and flexible class of equivariant convolutional networks. We show that steerable CNNs achieve state of the art results on the CIFAR image classification benchmark. The mathematical theory of steerable representations reveals a type system in which any steerable representation is a composition of elementary feature types, each one associated with a particular kind of symmetry. We show how the parameter cost of a steerable filter bank depends on the types of the input and output features, and show how to use this knowledge to construct CNNs that utilize parameters effectively.
Towards a Data Warehouse Architecture for Managing Big Data Evolution

The problem of designing data warehouses in accordance with user requirements and adapting its data and schemata to changes in these requirements as well as data sources has been studied by many researchers worldwide in the context of relational database environments. However, due to the emergence of big data technologies and the necessity to perform OLAP analysis over big data, innovative methods must be developed also to support evolution of data warehouse that is used to analyse big data. Therefore, the main objective of this paper is to propose a data warehousing architecture over big data capable of automatically or semi-automatically adapting to user needs and requirements as well as to changes in the underlying data
An offset-tolerant current-sampling-based sense amplifier for Sub-100nA-cell-current nonvolatile memory

Decreasing read cell current (ICELL) has become a key trend in nonvolatile memory (NVM). This is not only due to device size and VDD scaling while keeping the same threshold voltage (VTH), but also to the growing spread of the following applications: 1) multiple-level-cell (MLC) [1–2] to achieve smaller area-per-bit; 2) lower-VDD  to save power consumption; 3) Logic-process-compatible onetime programming memories (OTP) for embedding into mobile chips. A smaller ICELL leaves the sense amplifiers (SAs) operation vulnerable to 1) bitline (BL) level offset due to noise, bias and load (CBL) mismatches and 2) VTH variation. As device size and BL-pitch is continually scaled down, the above factors have become major showstopper for SAs. To tolerate these offsets, small-ICELLNVMs suffer from slow read speed or high read fail probability. Thus, a more largely offset tolerant SA is a prerequisite to achieve faster read speeds. In this study, we propose a new offset tolerant current-sampling-based SA (CSB-SA) to achieve 7× faster read speed than previous SAs for sensing small ICELL. A fabricated 90nm 512Kb OTP macro, using the CSB-SA and our CMOS-logic-compatible OTP cell , achieves 26ns macro random access time for reading sub-200nA ICELL. Measurements also confirmed that this 90nm CSB-SA could achieve sub-100nA sensing.
Lactic Acid Bacteria and Their Bacteriocins: Classification, Biosynthesis and Applications against Uropathogens: A Mini-Review

Several lactic acid bacteria (LAB) isolates from the Lactobacillus genera have been applied in food preservation, partly due to their antimicrobial properties. Their application in the control of human pathogens holds promise provided appropriate strains are scientifically chosen and a suitable mode of delivery is utilized. Urinary tract infection (UTI) is a global problem, affecting mainly diabetic patients and women. Many uropathogens are developing resistance to commonly used antibiotics. There is a need for more research on the ability of LAB to inhibit uropathogens, with a view to apply them in clinical settings, while adhering to strict selection guidelines in the choice of candidate LAB. While several studies have indicated the ability of LAB to elicit inhibitory activities against uropathogens in vitro, more in vivo and clinical trials are essential to validate the efficacy of LAB in the treatment and prevention of UTI. The emerging applications of LAB such as in adjuvant therapy, oral vaccine development, and as purveyors of bioprotective agents, are relevant in infection prevention and amelioration. Therefore, this review explores the potential of LAB isolates and their bacteriocins to control uropathogens, with a view to limit clinical use of antibiotics.
MOMM: Multi-objective model merging

Nowadays, software systems are complex and large. To cope with this situation, teams of developers have to cooperate and work in parallel on software models. Thus, techniques to support the collaborative development of models are a must. To this end, several approaches exist to identify the change operations applied in parallel, to detect conflicts among them, as well as to construct a merged model by incorporating all non-conflicting operations. Conflicts often denote situations where the application of one operation disables the applicability of another one. Consequently, one operation has to be omitted to construct a valid merged model in such scenarios. When having to decide which operation to omit, the importance of their application, depending on the operation type and the application context, has to be taken into account. However, existing work treat the operations to merge with equal importance. We introduce in this paper, for the first time, a multi-objective formulation of the problem of model merging, based on NSGA-II, that aims to find the best trade-off between minimizing the number of omitted operations and maximizing the number of successfully applied important operations. We evaluated our approach using seven open source systems and compared it with different existing model merging approaches. The merging solutions obtained with our approach were found in 100% of the scenarios of our experiments to be comparable in terms of minimizing the number of conflicts to those suggested by existing approaches and to carry a high importance score of merged operations. Our results also revealed an interesting feature about the trade-off between the two conflicting objectives that demonstrates the practical value of taking the importance of operations into account in model merging tasks since the shape of the Pareto front represents an interesting guidance for developers to select best solutions based on their preferences.
Substrate-Independent Microwave Components in Substrate Integrated Waveguide Technology for High-Performance Smart Surfaces

Although all existing air-filled substrate integrated waveguide (AFSIW) topologies yield a substrate-independent electrical performance, they rely on dedicated, expensive, laminates to form air-filled regions that contain the electromagnetic fields. This paper proposes a novel substrate-independent AFSIW manufacturing technology, enabling straightforward integration of high-performance microwave components into a wide range of general-purpose commercially available surface materials by means of standard additive (3-D printing) or subtractive (computer numerically controlled milling/laser cutting) manufacturing processes. First, an analytical formula is derived for the effective permittivity and loss tangent of the AFSIW waveguide. This allows the designer to reduce substrate losses to levels typically encountered in high-frequency laminates. Then, several microwave components are designed and fabricated. Measurements of multiple AFSIW waveguides and a four-way power divider/combiner, both relying on a new coaxial-to-air-filled SIW transition, prove that this novel approach yields microwave components suitable for direct integration into everyday surfaces, with low insertion loss, and excellent matching and isolation over the entire [5.15–5.85] GHz band. Hence, this innovative approach paves the way for a new generation of cost-effective, high-performance, and invisibly integrated smart surface systems that efficiently exploit the area and the materials available in everyday objects.
Escrow Protocols for Cryptocurrencies: How to Buy Physical Goods Using Bitcoin

We consider the problem of buying physical goods with cryptocurrencies. There is an inherent circular dependency: should be the buyer trust the seller and pay before receiving the goods or should the seller trust the buyer and ship the goods before receiving payment? This dilemma is addressed in practice using a third party escrow service. However, we show that naive escrow protocols introduce both privacy and security issues. We formalize the escrow problem and present a suite of schemes with improved security and privacy properties. Our schemes are compatible with Bitcoin and similar blockchain-based cryptocurrencies.
The Authentic Personality : A Theoretical and Empirical Conceptualization and the Development of the Authenticity Scale

This article describes the development of a measure of dispositional authenticity and tests whether authenticity is related to well-being, as predicted by several counseling psychology perspectives. Scales were designed to measure a tripartite conception of authenticity, comprising self-alienation, authentic living, and accepting external influence, which was supported with exploratory factor analysis. Multigroup confirmatory factor analysis showed that the factor loadings were invariant across sample, ethnicity, and gender. The scale showed substantial discriminant validity from the Big Five personality traits, nonsignificant correlations with social desirability, and 2and 4-week test–retest correlations ranging from r .78 to .91. Each subscale was strongly related to self-esteem and aspects of both subjective and psychological well-being. This article provides the first direct test of several theoretical models that view authenticity as integral to well-being.
Planning as satisfiability: Heuristics

Reduction to SAT is a very successful approach to solving hard combinatorial problems in Artificial Intelligence and computer science in general. Most commonly, problem instances reduced to SAT are solved with a general-purpose SAT solver. Although there is the obvious possibility of improving the SAT solving process with application-specific heuristics, this has rarely been done successfully. In this work we propose a planning-specific variable selection strategy for SAT solving. The strategy is based on generic principles about properties of plans, and its performance with standard planning benchmarks often substantially improves on generic variable selection heuristics, such as VSIDS, and often lifts it to the same level with other search methods such as explicit state-space search with heuristic search algorithms.
Internet Addiction : Personality Traits Associated with Its Development

This study investigated personality traits of those considered dependent users of the Internet utilizing the 16PF. Results showed that 259 cases of Dependents were classified based upon modified DSM-IV criteria for Pathological Gambling. Dependents ranked high in terms of selfreliance, emotional sensitivity and reactivity, vigilance, low self-disclosure, and non-conformist characteristics. This preliminary analysis discusses how such traits may act as triggers of addiction in order to fulfill an unmet psychological need through on-line stimulation.
Ransomware: A Rising Threat of new age Digital Extortion

Compared to the last five to six years, the massive scale by which innocent users are being subjected to a new age threat in form of digital extortion has never been seen before. With the rise of Internet, use of personal computers and devices has mushroomed to immense scale, with cyber criminals subjecting innocent users to extortion using malware. The primary victim to be hit the most has been online banking, impacting the security and reputation of banking and financial transactions along with social interactions. Online security revolves around three critical aspects – starting with the use of digital data and files, next with the use of computer systems and finally the internet as an unsecure medium. This is where Ransomware has become one of the most malicious form of malware for digital extortion threats to home and corporate user alike. Akashdeep Bhardwaj UPES Dehradun, India
A Probabilistic Model for Exteriors of Residential Buildings

We propose a new framework to model the exterior of residential buildings. The main goal of our work is to design a model that can be learned from data that is observable from the outside of a building and that can be trained with widely available data such as aerial images and street-view images. First, we propose a parametric model to describe the exterior of a building (with a varying number of parameters) and propose a set of attributes as a building representation with fixed dimensionality. Second, we propose a hierarchical graphical model with hidden variables to encode the relationships between building attributes and learn both the structure and parameters of the model from the database. Third, we propose optimization algorithms to generate three-dimensional models based on building attributes sampled from the graphical model. Finally, we demonstrate our framework by synthesizing new building models and completing partially observed building models from photographs.
Women's use of cosmetics: psychosocial correlates and consequences.

Synopsis Few systematic studies have examined individual differences in women's use of facial make-up or the possible psychosocial effects of such use. In the present investigation, the researchers developed several measures of the amount and the situational and temporal patterning of cosmetics use. Among forty-two female college students, differential use was associated with a number of selected personality variables-public self-consciousness, public body-consciousness, social anxiety, and various body-image factors. Through the imagery-induction of cosmetics use and non-use conditions, cosmetics users' self-evaluative responses were studied. In a variety of imagined situations, subjects reported being more self-confident and sociable when wearing as opposed to not wearing their customary cosmetics. Findings were discussed in the context of the role of cosmetics in self-image enhancement and social impression management.
Age estimation via face images: a survey

Facial aging adversely impacts performance of face recognition and face verification and authentication using facial features. This stochastic personalized inevitable process poses dynamic theoretical and practical challenge to the computer vision and pattern recognition community. Age estimation is labeling a face image with exact real age or age group. How do humans recognize faces across ages? Do they learn the pattern or use age-invariant features? What are these age-invariant features that uniquely identify one across ages? These questions and others have attracted significant interest in the computer vision and pattern recognition research community. In this paper, we present a thorough analysis of recent research in aging and age estimation. We discuss popular algorithms used in age estimation, existing models, and how they compare with each other; we compare performance of various systems and how they are evaluated, age estimation challenges, and insights for future research.
An analysis of various snort based techniques to detect and prevent intrusions in networks proposal with code refactoring snort tool in Kali Linux environment

Security and reliability are the major concern of our daily life usage of any network. But with the swift advancements in network technology, attacks are becoming more sophisticated than defenses. Although firewalls and router-based packet filtering are essential elements of an overall network security topology, they are not enough on their own. So, to brace the network from unauthorized access the idea of Intrusion Detection System (IDS) and Intrusion Prevention System (IPS) is attracting security experts. This paper briefs various trends in Intrusion Detection & Prevention. To understand various techniques in IDS, this paper analyses various approaches proposed by security researchers specifically using popular open source software Snort as their IDS tool. Being an open source IDS, Snort can be easily configured and deployed in any environment. To assess the efficiency, these research papers are analyzed in various performance aspects like Detection Accuracy, Scalability and Capability of detecting unknown attacks. To overcome various challenges like low detection rate, incapable of handling huge traffic, unsupported automated tuning, etc. that are identified during literature review, this paper proposes a level based architecture. All the levels are designed as incremental i.e. capable of providing the desired functionality and also its lower levels. To prove the efficiency of the proposed architecture, it can be integrated into Snort Tool using Code Refactoring. Also proposed an environment setup to evaluate the modified Snort Tool performance in future.
Popularity prediction of images and videos on Instagram

We live in a world surrounded by numerous social media platforms, applications and websites which produce various texts, images and videos (posts) daily. People share their moments with their friends and families via these tools to keep in touch. This extensiveness of social media has led to an expansion of information in various forms. It is difficult to imagine someone totally unfamiliar with these concepts and not having posted any content on a platform. All users, ranging from individuals to large companies, want to get the most of their audiences' attention. Nevertheless, the problem is that not all these posts are admired and noticed by their audience. Therefore, it would be important to know what characteristics a post should have to become the most popular. Studying this enormous data will develop a knowledge from which we can understand the best way to publish our posts. To this end, we gathered images and videos from Instagram accounts and we used some image/video context features to predict the number of likes a post obtains as a meaning of popularity through some regression and classification methods. By the experiments with 10-fold cross-validation, we get the results of Popularity Score prediction with 0.002 in RMSE and Popularity Class prediction with 90.77% accuracy. As we know, this study is the first exploring of Iranian Instagram users for popularity prediction.
Implementation of RFID on Computer Based Test (RF-CBT) system

The paper presents an improvement of assessment model using RFID (Radio Frequency Identification) technology which implemented on Computer Based Test (CBT). The RFID worked at frequency 13.56 MHz. The RF-CBT system is constructed with User-PC and Server-PC. A RFID reader module (Mifare RC522, Microcontroller ATMEGA328) and LabVIEW program are installed on User-PC. An RFID tag information from User-PC was sent into Server-PC which is installed with MySQL database and PHP. The registered RFID tag on Server-PC could log in the CBT automatically. Our system is proposed not only for auto login to CBT but also for developing a random question and scoring test result on CBT. The system could reduce the opportunity to cheat in test as anyone cannot login to the test except have the authentic RFID tag. This system is feasible to measure students' cognitive abilities at once because it uses multiple choices test type.