nils-herrmann/clean_scirepeval huggingface dataset:
Analysis of Student Understanding of Basic AC Concepts

This project has progressed in multiple stages. In the first year of the project we studied student understanding of basic concepts related to voltage, current, and power in the domain of DC and AC circuits. Protocol analyses conducted in the context of problem solving tasks demonstrated that electricity is a hard domain to learn and understand, and most beginning student knowledge is "in pieces." Students had difficulty in differentiating key concepts such as voltage and current, lacked the ability to map from physical processes to abstract notation, and experienced problems because they had incomplete mappings for metaphors and analogies. Tlie "invisible nature" of electricity contributed to the complexity of the domain. Students, in general, had very few preconceived notions about electricity, and most of what they learned was gained through instruction. In year two, our emphasis shifted to a study of how to prepare students to learn DC and AC circuit concepts they had difficulty with, and then to assess how instruction in these topics improved problem solving behavior. Tliis led to the development of our framework for Assessment of Domain Learnability (ADL) and the implementation of a computer environment, STAR-Legacy, that integrates instruction with dynamic assessment. Preliminary studies depict the effectiveness of this approach in improving student problem solving capability in the DC circuit domain. To further characterize problem solving ability with more advanced AC concepts we developed a set of problems dealing with voltage regulators and filters and performed protocol studies on a set of undergraduate and graduate students at Vanderbilt University:. The results of this study are also reported.
Function-Hiding Inner Product Encryption

We extend the reach of functional encryption schemes that are provably secure under simple assumptions against unbounded collusion to include function-hiding inner product schemes. Our scheme is a private key functional encryption scheme, where ciphertexts correspond to vectors ~x, secret keys correspond to vectors ~y, and a decryptor learns 〈~x, ~y〉. Our scheme employs asymmetric bilinear maps and relies only on the SXDH assumption to satisfy a natural indistinguishability-based security notion where arbitrarily many key and ciphertext vectors can be simultaneously changed as long as the key-ciphertext dot product relationships are all preserved.
A study of strategy implementation as expressed through Sun Tzu's principles of war

Business managers are facing the dynamic environment nowadays, and encountering more and more difficulties in decision-making. In order to formulate suitable strategies, they must consider all aspects of dynamic environments and situations which they meet. Sun Tzu's The Art of War is probably the oldest military book in Chinese and the principles which Sun Tzu advocated are still valuable in many business operations. When business managers can apply Sun Tzu's principles into consideration in strategic decision-making, they will create more and more strategies and methods in solving the countless problems. This investigation will be focused on the top 200 largest corporations in Taiwan and the purposes of this study are as follows: (1) To evaluate which principles of Sun Tzu's The Art of War could be applied in the real business enterprises when business managers formulate their competitive strategies, (2) To evaluate whether different kinds of firms adopt different Sun Tzu's principles, (3) To investigate how the levels of adoptions on Sun Tzu's principles of situation appraisal, strategy implementation, and strategic control impact on a firm's acquiring its key success factors and achieving its business performances. Results of this study are as follows. 1. Sun Tzu's principles of war can be used in strategic management and business operations. It has been shown that there are significant interrelationships between Sun Tzu's principles of situation appraisal, strategy implementation, and strategic control. 2. If firms' adoptions of Sun Tzu's principles of situation appraisal, strategy implementation and strategic control are higher, it will be easier for them to acquire their key success factors, and their business performances will be great. 3. Firm in high-tech industries most adopt Sun Tzu's principles of situation appraisal, strategy implementation, and strategic control in business operation, and they easily acquire their key success factors. Therefore, their business performances are usually better. 4. The higher firms adopt Sun Tzu' principles of internal environment appraisal in situation appraisal, adaptability in strategy implementation, security in strategic control, the easer do they get the marketing ability as their key success factors. Also their business performances will be better. · ½ ¡ CÁ ö µ M¡ u® ] ¤ l § Lª k¡ v¬ O¤ ¤ ° ê ³ Ì ¥ j¦ Ñ ª º § Lª k¨å Ä y¡ A¦ ý ¨ ä ¤ ¤ © Ò ´ £ ¨ ì ª º ¦ h ¶ µ-ì « h¤´µ M¯ à ³ Q …
A complete multi-robot path-planning algorithm

In the domain of multi-robot path-planning problems, robots must move from their start locations to their goal locations while avoiding collisions with each other. The research problem that we addressed is to find a complete solution for the multi-robot path-planning problem. Our first contribution is to recognize the solvable instances of the problem with our solvability test; the theoretical analysis has already been provided to show the validity of this test. Our second contribution is to solve this problem completely, in polynomial time, with the Push and Spin (PASp) algorithm. Once the problem was solved, we found decisions within the complete solution that may improve the performance of the complete algorithm. Hence, our third contribution is to improve the performance by selecting the best path from the set of complete paths. We refer to the improved version of our algorithm as the improved PASp algorithm. In terms of the completeness evaluation, the mathematical proofs demonstrate that the PASp is a complete algorithm for a wider class of problem instances than the classes solved by the Push and Swap (PAS), Push and Rotate (PAR), Bibox or the tractable multi-robot path-planning (MAPP) algorithms. Moreover, PASp solves any graph recognized to be solvable without any assumptions. In addition, the theoretical proof of the PASp algorithm showed completive polynomial performance in terms of total-path-lengths and execution time. In our performance evaluation, the experimental results showed that the PASp performs competitively, in reasonable execution time, in terms of number of moves compared to the PAS, PAR, Bibox and MAPP algorithms on a set of benchmark problems from the video-game industry. In addition, the results showed the scalability and robustness of PASp in problems that can be solved only by PASp. Such problems require high levels of coordination with an efficient number of moves and short execution time. In grid and bi-connected graphs with too many cycles, PASp required more moves and more time than the PAS, PAR and Bibox algorithms. However, PASp is the only algorithm capable of solving such instances with only one unoccupied vertex. Furthermore, adding heuristic search and smooth operation to the improved PASp showed significant further improvement by reducing the number of moves for all problem instances. PASp produced the best plans in a bit higher time. Finally, the PASp algorithm solves a wider class of problems and performs more completely in very complex/crowded environments than other state-of-art algorithms. Additionally, the Spin operation introduces a novel swapping technique to exchange two items and restore others in a graph for industrial applications.
Effect of Information and Communication Technology-induced Multitasking on Academic Performance of University Students in Uganda

Numerous researches on information and communication technology (ICT)-induced multitasking among students document a number of unfavourable consequences, such as heightened distraction and less attention, hampered learning and hindered productivity at the expense of better academic performance. This study focused on the effect of information and communication technology induced multitasking on academic performance of university students in Uganda. To this end, primary data were collected during the month of May 2016 using stratified cluster sample design. A self-reported questionnaire was used to collect data from 312 students of Makerere University who participated in the study. Through structural equation modelling (SEM), it was demonstrated that ICT-induced multitasking does not affect academic performance directly but through self-regulation, attention span, emotional control and productivity focus. Nonetheless, multitasking does not always have negative consequences. To a majority of students, multitasking provides emotional satisfaction and enjoyment, which do correlate positively with good academic performance. Indeed, multitasking can be an effective use of time when well-regulated and an efficient tool in problem solving. Multitasking may only be indicative of the changing nature of norms. Traditionally, one was expected to give and receive undivided attention when talking in a face-to-face conversation with another; yet new norms are evolving for the networked society, such as responding to text messages promptly. To buffer the negative effect of ICT-induced multitasking on academic performance, one needs a facility with a good degree of self-regulation, attention span, emotional control and productivity focus.
Footprint of uncertainty for type-2 fuzzy sets

In the paper, a new and comprehensible definition is proposed for type-2 fuzzy sets (T2 FSs), and the primary and secondary memberships function are defined respectively by using multi valued mapping. A new definition and formula for the footprint of uncertainty (FOU) is presented, and based on the new definitions, the relation between FOU and the original definition of T2 FS is discussed. Finally, the partition method of FOU is provided to represent the primary membership grade, the FOU and the interval type-2 fuzzy sets (IT2 FS) when the upper and lower membership functions (UMF, LMF) of FOU are given.
EnergyPatch: Repairing Resource Leaks to Improve Energy-Efficiency of Android Apps

Increased usage of mobile devices, such as smartphones and tablets, has led to widespread popularity and usage of mobile apps. If not carefully developed, such apps may demonstrate energy-inefficient behaviour, where one or more energy-intensive hardware components (such as Wifi, GPS, etc) are left in a high-power state, even when no apps are using these components. We refer to such kind of energy-inefficiencies as energy bugs. Executing an app with an energy bug causes the mobile device to exhibit poor energy consumption behaviour and a drastically shortened battery life. Since mobiles apps can have huge input domains, therefore exhaustive exploration is often impractical. We believe that there is a need for a framework that can systematically detect and fix energy bugs in mobile apps in a scalable fashion. To address this need, we have developed EnergyPatch, a framework that uses a combination of static and dynamic analysis techniques to detect, validate and repair energy bugs in Android apps. The use of a light-weight, static analysis technique enables EnergyPatch to quickly narrow down to the potential program paths along which energy bugs may occur. Subsequent exploration of these potentially buggy program paths using a dynamic analysis technique helps in validations of the reported bugs and to generate test cases. Finally, EnergyPatch generates repair expressions to fix the validated energy bugs. Evaluation with real-life apps from repositories such as F-droid and Github, shows that EnergyPatch is scalable and can produce results in reasonable amount of time. Additionally, we observed that the repair expressions generated by EnergyPatch could bring down the energy consumption on tested apps up to 60 percent.
Bayesian modelling of Jumping-to-Conclusions bias in delusional patients.

When deciding about the cause underlying serially presented events, patients with delusions utilise fewer events than controls, showing a "Jumping-to-Conclusions" bias. This has been widely hypothesised to be because patients expect to incur higher costs if they sample more information. This hypothesis is, however, unconfirmed.  The hypothesis was tested by analysing patient and control data using two models. The models provided explicit, quantitative variables characterising decision making. One model was based on calculating the potential costs of making a decision; the other compared a measure of certainty to a fixed threshold.  Differences between paranoid participants and controls were found, but not in the way that was previously hypothesised. A greater "noise" in decision making (relative to the effective motivation to get the task right), rather than greater perceived costs, best accounted for group differences. Paranoid participants also deviated from ideal Bayesian reasoning more than healthy controls.  The Jumping-to-Conclusions Bias is unlikely to be due to an overestimation of the cost of gathering more information. The analytic approach we used, involving a Bayesian model to estimate the parameters characterising different participant populations, is well suited to testing hypotheses regarding "hidden" variables underpinning observed behaviours.
A logistics demand forecasting model based on Grey neural network

Logistics demand forecasting is important for investment decision-making of infrastructure and strategy programming of the logistics industry. In this paper, a hybrid method which combines the Grey Model, artificial neural networks and other techniques in both learning and analyzing phases is proposed to improve the precision and reliability of forecasting. After establishing a learning model GNNM(1,8) for road logistics demand forecasting, we chose road freight volume as target value and other economic indicators, i.e. GDP, production value of primary industry, total industrial output value, outcomes of tertiary industry, retail sale of social consumer goods, disposable personal income, and total foreign trade value as the seven key influencing factors for logistics demand. Actual data sequences of the province of Zhejiang from years 1986 to 2008 were collected as training and test-proof samples. By comparing the forecasting results, it turns out that GNNM(1,8) is an appropriate forecasting method to yield higher accuracy and lower mean absolute percentage errors than other individual models for short-term logistics demand forecasting.
Egg-trapping of black soldier fly , Hermetia illucens ( L . ) ( Diptera : Stratiomyidae

Black soldier fly (BSF), Hermetia illucens (L.) is widely used in bio-recycling of human food waste and manure of livestock. Eggs of BSF were commonly collected by egg-trapping technique for mass rearing. To find an efficient lure for BSF egg-trapping, this study compared the number of egg batch trapped by different lures, including fruit, food waste, chicken manure, pig manure, and dairy manure. The result showed that fruit wastes are the most efficient on trapping BSF eggs. To test the effects of fruit species, number of egg batch trapped by three different fruit species, papaya, banana, and pineapple were compared, and no difference were found among fruit species. Environmental factors including temperature, relative humidity, and light intensity were measured and compared in different study sites to examine their effects on egg-trapping. The results showed no differences on temperature, relative humidity, and overall light intensity between sites, but the stability of light environment differed between sites. BSF tend to lay more eggs in site with stable light environment.
Cytosolic DNA Sensing Promotes Macrophage Transformation and Governs Myocardial Ischemic Injury.

Myocardium irreversibly injured by ischemic stress must be efficiently repaired to maintain tissue integrity and contractile performance. Macrophages play critical roles in this process. These cells transform across a spectrum of phenotypes to accomplish diverse functions ranging from mediating the initial inflammatory responses that clear damaged tissue to subsequent reparative functions that help rebuild replacement tissue. Although macrophage transformation is crucial to myocardial repair, events governing this transformation are poorly understood.



Here, we set out to determine whether innate immune responses triggered by cytoplasmic DNA play a role.



We report that ischemic myocardial injury, along with the resulting release of nucleic acids, activates the recently described cyclic GMP-AMP synthase-stimulator of interferon genes pathway. Animals lacking cyclic GMP-AMP synthase display significantly improved early survival after myocardial infarction and diminished pathological remodeling, including ventricular rupture, enhanced angiogenesis, and preserved ventricular contractile function. Furthermore, cyclic GMP-AMP synthase loss of function abolishes the induction of key inflammatory programs such as inducible nitric oxide synthase and promotes the transformation of macrophages to a reparative phenotype, which results in enhanced repair and improved hemodynamic performance.



These results reveal, for the first time, that the cytosolic DNA receptor cyclic GMP-AMP synthase functions during cardiac ischemia as a pattern recognition receptor in the sterile immune response. Furthermore, we report that this pathway governs macrophage transformation, thereby regulating postinjury cardiac repair. Because modulators of this pathway are currently in clinical use, our findings raise the prospect of new treatment options to combat ischemic heart disease and its progression to heart failure.
Beam Division Multiple Access (BDMA) and modulation formats for 5G: Heir of OFDM?

The paper throws light on Beam Division Multiple Access (BDMA) technique and various possible heirs of Orthogonal Frequency Division Multiplexing (OFDM) as modulation schemes anticipated to be used in futuristic 5G communications. This paper emphasizes on the concept of BDMA, a multiple access technique to overcome the limitations of existing frequency and time resource based access techniques for multiple access of same channel. The possible modulation schemes such as Filter Bank Multicarrier (FBMC), Faster Than Nyquist (FTN) signaling and Single Carrier Modulations (SCMs) that can be heir of OFDM are studied, simulated and a comparison of these techniques is done based on the simulation results. Possible application scenarios of OFDM heirs with respect to 5G implementation requirements are also proposed.
Consumer Attitude towards Cosmetic Products *

The world wide annual expenditures for cosmetics is estimated at U.S.$18 billion, and many players in the field are competing aggressively to capture more and more market. Hence, companies are interested to know about consumer’s attitude towards cosmetics so as to devise strategies to win over competition. The main purpose of this article is to investigate the influence of attitude on cosmetics buying behaviour. The research question is “what kind of attitudes do the customers have towards buying behaviour of cosmetic products?” A questionnaire was developed and distributed to female consumers in Bangalore city by using convenience sampling method. 118 completed questionnaires were returned and then 100 valid were analyzed by using ANOVA, mean and standard deviation. The result of the study confirms that age, occupation, marital status have positive influence towards cosmetic products. But income does not have any influence on the attitude towards cosmetic products.
Development of a Skin-Like Tactile Sensor Array for Curved Surface

In this paper, we develop a skin-like tactile sensor array to measure the contact pressure of curved surfaces. The sensor array is laminated into a thin film 3 mm in thickness and can easily be wrapped around a pencil without damaging its skin-like structure. So far, we have achieved the array containing 8 × 16 sensor elements. Its spatial resolution is 1 element per 9 mm2 area and it can measure the pressure up to 360 kPa. The sensor-array patch contains three layers. The upper and lower layers are polydimethylsiloxane (PDMS) thin films embedded with the conductor strips formed by PDMS-based silver nanowires (AgNWs) networks. The middle layer is formed by the mixing of nickel powder with liquid PDMS for contact force measurement. Experimental tests have demonstrated that conductor strips on the upper layer can maintain their resistances ~ 23 Ω with increase when the tensile strain is up to 50%. Noted is the conductor made with carbon nanotubes can keep its conductivity unchanged for up to only 40% tensile strain. Through fatigue tests, it is observed that the measured AgNWs/PDMS conductor strip exhibits low and stable resistances. This is one of the most desired behaviors of the stretchable interconnects for signal transmission. The integrated sensor system can successfully measure the contact pressure induced by objects of different shapes. It can be applied on curved or non-planar surfaces in robots or medical devices for force detection and feedback.
Investigations on Active Balancing Circuits for Supercapacitor Banks

The present paper continues our investigations in the field of Supercapacitors or Electrochemical Double Layer Capacitors, briefly named EDLCs. The series connection of EDLCs is usual in order to obtain higher voltage levels. The inherent uneven state of charge (SOC) and manufacturing dispersions determine during charging at constant current that one of the capacitors reaches first the rated voltage levels and could, by further charging, be damaged. The balancing circuit with resistors and transistors used to bypass the charging current can be improved using the proposed circuit. We present here a complex variant, based on integrated circuit acting similar to a microcontroller. The circuit is adapted from the circuits investigated in the last 7–8 years for the batteries, especially for Lithium-ion type. The test board built around the circuit is performant, energy efficient and can be further improved to ensure the balancing control for larger capacitances.
Multiple Event Detection and Recognition for Large-Scale Power Systems Through Cluster-Based Sparse Coding

Accurate event analysis in real time is of paramount importance for high-fidelity situational awareness such that proper actions can take place before any isolated faults escalate to cascading blackouts. Existing approaches are limited to detect only single or double events or a specified event type. Although some previous works can well distinguish multiple events in small-scale systems, the performance tends to degrade dramatically in large-scale systems. In this paper, we focus on multiple event detection, recognition, and temporal localization in large-scale power systems. We discover that there always exist “regions” where the reaction of all buses to certain event within each region demonstrates high degree similarity, and that the boundary of the “regions” generally remains the same regardless of the type of event(s). We further verify that, within each region, this reaction to multiple events can be approximated as a linear combination of reactions to each constituent event. Based on these findings, we propose a novel method, referred to as cluster-based sparse coding (CSC), to extract all the underlying single events involved in a multievent scenario. Multiple events of three typical disturbances (e.g., generator trip, line trip, and load shedding) can be detected and recognized. Specifically, the CSC algorithm can effectively distinguish line trip events from oscillation, which has been a very challenging task for event analysis. Experimental results based on simulated large-scale system model (i.e., NPCC) show that the proposed CSC algorithm presents high detection and recognition rate with low false alarms.