Reviewerly/exHarmony huggingface dataset:
The Engineering Professor Of 2020: The Forgotten Variable

Much has been said about the profile of the engineering graduate of the future and about effective and innovative teaching and learning strategies, yet only a few have spoken about the skills and competencies of the ideal engineering professor -key individual of the heart of the process education process.How can engineering faculty instill the novel skills and competencies of the profession if they themselves do not possess these, have never experienced real-life engineering, and do not consciously study their own teaching methods?Engineering education gathers experts that blend two professions -engineering and education.Thus, engineering professors need to be both engineers AND educators and be trained and/or have experience in both disciplines.Engineering educators need to both understand what it takes to practice the engineering profession and how to effectively catalyze student learning.If we are requiring students to engage in real-life, practice-based learning experiences (co-op, internships, etc.), shouldn't this be also a required activity for those teaching students?This paper shares the results of an informal survey on the skills and competencies of the ideal engineering professor done in the Fall of 2009 among students, faculty/deans and industry members.The paper aims to initiate a dialogue among engineering education leaders around the "forgotten variable" in the education process: the set of desired skills and competencies of an ideal engineering professor.It hopes to kick off discussions around the following questions: What does the nascent engineer of 2020 need from his or her professor?What should the profile, skills and competencies of the engineering educator of 2020 be?Why has the current system allowed us to forget this critical variable, and how can we grow these skills in engineering faculty?Furthermore, how can we nurture effective partnerships, develop capacity building programs and find the resources to bring a significant change in this most critical protagonist of engineering education?If these questions are answered jointly by all stakeholders and an action agenda is developed during the next few years -similar to the NAE Engineering of 2020 Report -one of the biggest challenges in creating a culture for innovation in engineering education will be addressed.
Crystallographic multiwavelets in $L^2(\mathbb {R}^d)$

We characterize the scaling function of a crystal Multiresolution Analysis in terms of the vector-scaling function for a Multiresolution Analysis associated to a lattice. We give necessary and sufficient conditions in terms of the symbol matrix in order that an associated crystal wavelet basis exists.
A two-stage estimation procedure for non-linear structural equation models

Summary Applications of structural equation models (SEMs) are often restricted to linear associations between variables. Maximum likelihood (ML) estimation in non-linear models may be complex and require numerical integration. Furthermore, ML inference is sensitive to distributional assumptions. In this article, we introduce a simple two-stage estimation technique for estimation of non-linear associations between latent variables. Here both steps are based on fitting linear SEMs: first a linear model is fitted to data on the latent predictor and terms describing the non-linear effect are predicted by their conditional means. In the second step, the predictions are included in a linear model for the latent outcome variable. We show that this procedure is consistent and identifies its asymptotic distribution. We also illustrate how this framework easily allows the association between latent variables to be modeled using restricted cubic splines, and we develop a modified estimator which is robust to non-normality of the latent predictor. In a simulation study, we compare the proposed method to MLE and alternative two-stage estimation techniques.
Influence of recent volcanism of the geochemical behaviour of trace elements and gases in deep granitic hydrothermal systems, southwest Bulgaria

This investigation is aimed at defining the geochemical behaviour of trace elements and gases in deep granitic geothermal systems in southwest Bulgaria. The influence of recent volcanic events on water-rock interaction in these systems is studied. The enrichment with CO2 imposes an important influence on the fluid composition and these modifications have important indicator possibilities. The processes of “water-rock” interaction lead to concentration of many trace elements in the aqueous phase. The experimental simulation of granite leaching yields the typical trace element rich aqueous phase, highlighting the secondary nature of the influence of the volcanic emanations. The complex modification of the composition is a reflection of the processes (primary and secondary) acting on the thermal fluid at depth.
Teacher’s Methodical Activity as a Source of Educational and Methodical Tasks

The article of S. Skvortsova “Teacher’s methodical activity as a source of educational and methodical tasks”, interprets the teacher’s methodical activity as solving a number of methodical tasks. We define a methodical task as a situation that occurs in the process of teacher's methodical activity the purpose of which is to teach pupils certain content. Educational and methodical tasks are the models of such situations formulated in words. The goal of educational and methodical tasks is to form future teachers’ methodical competency. Methodical tasks are classified under on practical and intellectual, that in its turn are divided into standard and problematic. Taking into consideration the external structure of the process of solving methodical tasks we define the teacher’s ability to solve methodical tasks as a complex of actions to be performed to solve a methodical task on the basis of a teacher’s conscious use of methodical knowledge and ways of action. Educational and methodical tasks are used in order to form the ability to solve methodical tasks in the process of teacher’s methodical training in pedagogical universities. Educational and methodical tasks, as opposed to methodical tasks, are classified according to: 1) the level of methodical activity as on standard, partially-standard and creative; 2) the types of methodical activity as on informational-analytical, analytic-synthetic, operationally-practical, projective-modeling, synthetic-constructing; 3) the content of teacher’s methodical activity as on basic and special ones.&#x0D; Standard and partially-standard educational and methodical tasks are the symbolic models of standard methodical tasks in teacher’s activity, and creative educational and methodical tasks are the symbolic models of problematic methodical tasks. Educational and methodical tasks are mainly the models of intellectual methodical tasks as they don’t suggest the interaction between a teacher and pupils, though, in some cases, they may be solved in the process of imitation of a teacher’s activity in the classroom environment
Protecting shared information in networks: A network security game with strategic attacks

Summary A digital security breach, by which confidential information is leaked, does not only affect the agent whose system is infiltrated but is also detrimental to other agents socially connected to the infiltrated system. Although it has been argued that these externalities create incentives to underinvest in security, this presumption is challenged by the possibility of strategic adversaries that attack the least protected agents. In this paper we study a new model of security games in which agents share tokens of sensitive information in a network of contacts. The agents have the opportunity to invest in security to protect against an attack that can be either strategically or randomly targeted. We show that, in the presence of random attack, underinvestments always prevail at the Nash equilibrium in comparison with the social optimum. Instead, when the attack is strategic, either underinvestments or overinvestments are possible, depending on the network topology and on the characteristics of the process of the spreading of information. Actually, agents invest more in security than socially optimal when dependencies among agents are low (which can happen because the information network is sparsely connected or because the probability that information tokens are shared is small). These overinvestments pass on to underinvestments when information sharing is more likely (and therefore, when the risk brought by the attack is higher). In order to keep our analysis tractable, some of our results on strategic attacks make an assumption of homogeneity in the network, namely, that the network is vertex‐transitive. We complement these results with an analysis on star graphs (which are nonhomogeneous), which confirms that the essential lines of our findings can remain valid on general networks.
“How to Rate a Video Game?” — A Prediction System for Video Games Based on Multimodal Information

Video games have become an integral part of most people's lives in recent times. This led to an abundance of data related to video games being shared online. However, this comes with issues such as incorrect ratings, reviews or anything that is being shared. Recommendation systems are powerful tools that help users by providing them with meaningful recommendations. A straightforward approach would be to predict the scores of video games based on other information related to the game. It could be used as a means to validate user-submitted ratings as well as provide recommendations. This work provides a method to predict the G-Score, that defines how good a video game is, from its trailer (video) and summary (text). We first propose models to predict the G-Score based on the trailer alone (unimodal). Later on, we show that considering information from multiple modalities helps the models perform better compared to using information from videos alone. Since we couldn't find any suitable multimodal video game dataset, we created our own dataset named VGD (Video Game Dataset) and provide it along with this work. The approach mentioned here can be generalized to other multimodal datasets such as movie trailers and summaries etc. Towards the end, we talk about the shortcomings of the work and some methods to overcome them.
On the Security of Jhanwar-Barua Identity-Based Encryption Scheme

In [3], Jhanwar and Barua presented an improvement of the Boneh-Gentry-Hamburg (BGH) scheme. In addition to reducing the time complexity of the algorithm to find a solution of the equation $$ax^2+Sy^2\equiv 1 \bmod n$$ , their scheme reduces the number of equations to be solved by combining existing solutions. In [2], Susilo et al. extended the Jhanwar-Barua scheme, reducing more the number of equations to be solved. This paper presents a security flaw that appears in both schemes and shows that they are not IND-ID-CPA secure.
REFERS: Refined &amp; Effective Fuzzy E-commerce Recommendation System

Online shopping culture is gaining traction globally and some of the biggest beneficiaries of this e-commerce shift are Amazon, eBay, etc. Recommendation systems guide online users in a personalised manner to choose what they want and their interest on each product present in the catalogue list. In such a scenario, the existing systems need complete information for making recommendations, which is not always possible in real applications. Therefore, a novel refined and effective fuzzy e-commerce recommendation system has been proposed in this paper that combines the benefits of difference in importance within the rating factors by a single user and new similarity measure approach that aims at improved recommendation list to the e-commerce user. The proposed methodology has been implemented using a new similarity measure on experimental datasets and the refined scores for such e-commerce website-based unlocked mobile phones are compared in this work against classic similarity measures.
Developing the Requirements of a PLM/ALM Integration: An Industrial Case Study

The digitization of the industry, the drive towards smart factories as well as the Internet of Production (IoP) require rising smartness of products and services. Smart physical products are often mechatronic products that include increasing amounts of software. The development of software, however, comes along with new challenges for companies specialized in developing mechanical, electrical or electronic products. Some of these challenges address the product lifecycle management (PLM)-related business and work processes. The management of software lifecycles requires a much more rigorous requirements management. Furthermore, special solutions for management of source code in distributed development teams are needed. The build-process and testing activities need to be conducted in a systematic manner. The generation and provision of different licensing models need to be mastered and finally the issue of security needs to be addressed for any product that can be networked—which by the way is a strategic target of nearly any product developing company. Application Lifecycle Management (ALM) covers many of the above-mentioned issues. IT solutions for ALM are comparable to traditional PLM solutions, but focus particularly on software as a product. Thus, these systems have become widely used by software companies in the same manner as PLM solutions belong to the standard enterprise IT environment of companies developing physical products. With software penetrating traditional physical products, product managers, product developers, manufacturing staff etc. need to work with both, PLM and ALM, since neither solution is able to cover both domains sufficiently. However, ALM and PLM solutions feature redundant functionality. Thus, best practices for the systematic integration of ALM and PLM are required.
Validation of a Simple Metabolic-Equivalent-of-Task Sensor Based on a Low-Cost NFC RFID Wristband

In this paper, a simple solution allowing continuous actimetry with an uniaxial magnetometer is presented. Worn on the wrist to monitor the forearm tilt, it can estimate the instantaneous metabolic-equivalent-of-task during physical activity. Autonomous acquisition and data transfer are managed by a radio frequency identification chip supporting the near field communication (NFC) standard. Thus, the solution can transfer measurements to an NFC-enabled device (computer and smartphone) that runs a custom algorithm. The algorithm output signal was indirectly calibrated to an accurate calorimetry device to display the real energy expenditure of the user during the physical activity session.
English Language Competence of Secretary Students through Report Writing: Corpus Based Study

This research is entitled “English Language Competence of Secretary Students through Report Writing:Corpus Based Study”. The main purpose of this research is to analyze the language competence of the Secretary Students in one of popular Academy Secretary in Bandung. The Language competence is something important for students in order to understand what they say or what they write. Every language competence implies meanings. Unfortunately not all students know how to understand the meanings through language. What they have in their minds that they have to write in good grammatical patterns. They keep busy memorizing the grammatical patterns without knowing the purpose of those patterns. This research uses the Corpus Linguistics method. This newly method is quite promising and interesting to implement in this research. The definition of Corpus Linguistics is used the theories which was proposed by McEnery and Wilson (1996,2001), Sinclair et al. (2004), Lindquist (2009), McEnery and Hardie (2012). In collecting data, the writer determined the keywords then found out the implementation of those words into their writing. There are 7 key words which are used by the students frequently. The result of this research shows that the students mostly use the elements of grammar such as determiner of “the” and “a”, preposition such as “in”, “on”, “about”; yet, they rarely implement those 7 keywords with any variation. Lack of using variation collocation to the keywords causing the ambiguity to the readers. Keywords: corpus linguistics, language competence, secretary, grammar, pattern
Making Hill-Climbing Great Again through Online Relaxation Refinement and Novelty Pruning

Delete relaxation is one of the most successful approaches to classical planning as heuristic search. The precision of these heuristics can be improved by taking some delete information into account, in particular through atomic conjunctions in the hCFF heuristic. It has recently been shown that this heuristic is especially effective when these conjunctions are learned online in a hill-climbing search algorithm. In this work, we devise a natural extension to this approach using novelty pruning, a recently-developed technique that prunes states based on whether they contain facts not seen before in the search. We evaluate our extension on the IPC benchmarks, where it beats LAMA, Mercury, and Dual-BFWS on many domains.
Predictive Analysis on Behavioural Risk Factor Surveillance System through Ensemble Classifiers and Clusters

The World Health Organization (WHO) has been asserting the importance of health care in today’s world. The objective of this research is to find out the type of medication that needs to be provided to the people at early stages to prevent behavioural risk factors. The health department of United States has a great vision to improve the immune system of the people and has taken measures to do the same through a Behavioural Risk Factor Surveillance System (BRFSS). This research aims to prevent behavioural risk factors by predictive analysis using the above mentioned dataset from the Centres for Disease Control and Prevention (CDC). The methods of ensemble classification and clustering is applied on the dataset, pre and post weighted classification, thereby classifying and prescribing the type of healthcare required for people exhibiting behaviours such as obesity, nutrition and physical activity. This analyses help improve the quality of health of the citizens. In an extensive study, it was observed that the result obtained was 92.87% accurate.
Analisis kinerja jaringan VANET dengan model propagasi free space dan two ray ground pada routing AODV

VANET is one type of Ad Hoc network that serves as a wireless network with several mobile nodes that do not have a fixed router. Each of these nodes can function as a router that can search and handle paths to other nodes within a network. Each node on the network is mobile so that the topology of the network is constantly changing. On a network, the routing protocol is something that has a lot of impact on the performance of the network.Each propagation model will certainly have different capabilities and characteristics, therefore it is necessary to research some propagation models in the specified place which will then affect QoS performance on the VANET network. Mobility simulation is done based on urban environment scenario that is around Malang City Hall. This research applies SUMO as mobile simulator and NS-2 as network simulator with AODV type reactive protocol as routing protocol which is used and use propagation model of Free Space and Two Ray Ground as comparison in NS-2.In this research to do QoS analysis with parameters in the test is End to End Delay, Jitter, Packet Delivery Ratio and Throughput. After the data collected, analysis is done by looking at the QoS between the propagation tested. The Free Space propagation model has a smaller delay time with an average of 0.1136 ms than on the Two Ray Ground propagation which has a value of 0.1696 ms. For the number of packets received successfully Free Space propagation is better with an average value of 482.06 kbps throughput compared to Two Ray Ground propagation. The results of testing and analysis prove that Free Space propagation is the right model on the VANET network used in urban environments.
Linear Kalman-Bucy filter with vector autoregressive signal and noise

The linear Kalman-Bucy filter problem for a system, at that a signal and a noise are vector independent stationary autoregressive processes with orders larger than 1, is investigated. The recurrent equations for filter and its error are delivered. The optimal way of the initial data definition is proposed. Some numerical examples are given. In one of them the algorithm leads to a stationary behavior at infinity. In the other example the Kalman- Bucy filter is impossible because the filter error goes to infinity. A behavior of a signal and its error is illustrated by a simulation of a signal and a noise as vector Gaussian stationary autoregressive processes. The simulation supports theoretical conclusions.
BootBandit: A macOS bootloader attack

Historically, the boot phase on personal computers left systems in a relatively vulnerable state. Because traditional antivirus software runs within the operating system, the boot environment is difficult to protect from malware. Examples of attacks against bootloaders include so‐called “evil maid” attacks, in which an intruder physically obtains a boot disk to install malicious software for obtaining the password used to encrypt a disk. The password then must be stored and retrieved again through physical access. In this paper, we discuss an attack that borrows concepts from the evil maid. We assume exploitation can be used to infect a bootloader on a system running macOS remotely to install code to steal the user's password. We explore the ability to create a communication channel between the bootloader and the operating system to remotely steal the password for a disk protected by FileVault 2. On a macOS system, this attack has additional implications due to “password forwarding” technology, in which a user's account password also serves as the FileVault password, enabling an additional attack surface through privilege escalation.
On Breiman’s dilemma in neural networks: phase transitions of margin dynamics

Margin enlargement over training data has been an important strategy since perceptrons in machine learning for the purpose of boosting the robustness of classifiers toward a good generalization ability. Yet Breiman shows a dilemma (Breiman, 1999) that a uniform improvement on margin distribution \emph{does not} necessarily reduces generalization errors. In this paper, we revisit Breiman's dilemma in deep neural networks with recently proposed spectrally normalized margins. A novel perspective is provided to explain Breiman's dilemma based on phase transitions in dynamics of normalized margin distributions, that reflects the trade-off between expressive power of models and complexity of data. When data complexity is comparable to the model expressiveness in the sense that both training and test data share similar phase transitions in normalized margin dynamics, two efficient ways are derived to predict the trend of generalization or test error via classic margin-based generalization bounds with restricted Rademacher complexities. On the other hand, over-expressive models that exhibit uniform improvements on training margins, as a distinct phase transition to test margin dynamics, may lose such a prediction power and fail to prevent the overfitting. Experiments are conducted to show the validity of the proposed method with some basic convolutional networks, AlexNet, VGG-16, and ResNet-18, on several datasets including Cifar10/100 and mini-ImageNet.