nils-herrmann/clean_scirepeval huggingface dataset:
ILFS: Intelligent Lost and Found System using Multidimensional Matching Model
Venue: 2019 IEEE SmartWorld, Ubiquitous Intelligence Computing, Advanced Trusted Computing, Scalable Computing Communications, Cloud Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI)
Year: 2019

Traditional lost and found system is based on content management, with low query efficiency and poor privacy. In our demonstration, we present an Intelligent Lost and Found System using Multidimensional Matching Model (ILFS) The front end of this system is WeChat applet, and the background platform takes the multidimensional matching algorithm as the core. The output of this system is matching result of Lost and Found. The innovation of ILFS is a multi dimensional matching model that protects user privacy and prevents malicious information from being publicized.
Inferring Fine grained Control Flow Inside SGX Enclaves with Branch Shadowing
Venue: USENIX Security Symposium
Year: 2017

Intel has introduced a hardware based trusted execution environment, Intel Software Guard Extensions (SGX) that provides a secure, isolated execution environment, or enclave, for a user program without trusting any underlying software (e.g. an operating system) or firmware. Researchers have demonstrated that SGX is vulnerable to a page fault based attack. However, the attack only reveals page level memory accesses within an enclave. In this paper, we explore a new, yet critical, side channel attack, branch shadowing, that reveals fine grained control flows (branch granularity) in an enclave. The root cause of this attack is that SGX does not clear branch history when switching from enclave to nonenclave mode, leaving fine grained traces for the outside world to observe, which gives rise to a branch prediction side channel. However, exploiting this channel in practice is challenging because 1) measuring branch execution time is too noisy for distinguishing fine grained controlflow changes and 2) pausing an enclave right after it has executed the code block we target requires sophisticated control. To overcome these challenges, we develop two novel exploitation techniques: 1) a last branch record (LBR) based history inferring technique and 2) an advanced programmable interrupt controller (APIC) based technique to control the execution of an enclave in a finegrained manner. An evaluation against RSA shows that our attack infers each private key bit with 99.8% accuracy. Finally, we thoroughly study the feasibility of hardware based solutions (i.e. branch history flushing) and propose a software based approach that mitigates the attack.
You Ji Hua Xue Pin Bu Tong Wen Du Xia (Guo Leng )Ye Ti Zheng Qi Ya Yu Ce Mo Xing De Jian Li Yu Ping Jie
Year: 2015

(Guo Leng )Ye Ti Zheng Qi Ya (PL)Shi Ping Jie Hua Xue Pin Zai Huan Jing Zhong Fen Pei Qian Yi He Gui Qu Xing Wei De Zhong Yao Can Shu PLJu You Jiao Qiang De Wen Du Yi Fu Xing Fa Zhan Yi Chong Neng Gou Jing Que Yu Ce Bu Tong Huan Jing Wen Du Xia Hua Xue Pin PLDe Fang Fa ,You Zhu Yu Tian Bu Hua Xue Pin Sheng Tai Feng Xian Ping Gu De Da Liang Shu Ju Que Shi Ben Yan  Du Xia (200~830 K)Gong Ji 10 478Ge log PLZhi Zai Ci Ji Chu Shang ,Cai Yong Pian Zui Xiao Er Cheng (PLS)Hui Gui He Zhi Chi Xiang Liang Ji (SVM)Fang Fa ,Gou Jian Liao PLDe Xian Xing He Fei Xian Xing Yu Ce Mo Xing Jie Guo Biao Ming :2Chong Mo Xing Jun Ju You Liang Hao De Ni He Du Wen Jian Xing Ji Yu Ce Neng Li ,SVMMo Xing De Yu Ce Xing Neng Lue Gao Yu PLSMo Xing (PLS:R2adj.tra=0.912,RMSEtra=0.477,Q2ext=0.910;SVM:R2adj.tra=0.997,RMSEtra=0.092,Q2ext=0.967) Ji Li Fen Xi Biao Ming ,Wen Du Shi Ying Xiang PLDe Zhu Yao Yin Su ,Wen Du Yue Gao ,Zheng Qi Ya Yue Da ;Qi Ci ,X1solYe Ying Xiang PLDa Xiao ,X1solYong Lai Miao Shu Fen Zi Jian De Se San Zuo Yong ,Fen Zi Jian Se San Li Yue Xiao ,Zheng Qi Ya Yue Da ;Ci Wai ,Hua He Wu De Qing Jian Ge Shu Ji Xing He Fen Zi Gou Xing Deng Yin Su Ye Ying Xiang PLDa Xiao Cai Yong Wiliams plotFang Fa Biao Zheng Liao PLSMo Xing Ying Yong Yu Suo Jian Li De Mo Xing Ke Yong Lai Yu Ce Wan Jing Xi Jing Chun Tong Zui Suan Ben Fen Lian Ben Lu Dai Fang Xiang Jing Han NHua He Wu Ji Han SHua He Wu Zai Bu Tong Wen Du Xia De PLShu Ju
An Experimental Study of Chinese English Major Students' Listening Anxiety of Classroom Learning Activity at the University Level
Year: 2010

Foreign language anxiety is one of the best predictors in accounting for individual differences in language learning success in SLA, and that it is proved to be one of the most essential and influential affective factors. The present study adopts English listening tests and questionnaire to conduct a survey on English listening classroom anxiety with 125 English majors as its subjects. The results show that there exist certain negative correlations both between English listening classroom anxiety and listening achievement. This thesis investigates the influence anxiety has on listening comprehension, explores the potential sources of foreign language listening anxiety, and puts forward some coping strategies from various aspects such as learners' psychology, teaching techniques, etc. in a hope to create a low anxiety classroom atmosphere, and help to improve students' listening performance and proficiency in a most favorable affective state.
Specifying the Design for Customer Learning in the Mixed Reality Experience
Year: 2019

Companies search for new ways of utilizing technologies such as the Mixed Reality (MR) in order to enrich their customer interactions. While more of these MR technologies are emerging to assist customer employee interactions, there is a strategic choice related to scalability of how to organize these service encounters: face to face or digitally over the web. Eventually, the question is how much of these interactions can be automatized with acceptable tradeoffs for the customer experience and business outcomes. This study analyzes the influence of a MR design elements on the outcomes of a customer experience in a use case where the customer learning is focal for the service. The experiment comparing two conditions: face to face interactions and remote interactions over the web showed no difference in terms of customer experience and perceived learning. On the other hand, the ease of use of the technology as well as the familiarity with the subject and technology effected the customer learning. The results offer implications to both the customer experience management and the MR system design.
Service recovery, customer satisfaction and customer loyalty: evidence from Malaysia's hotel industry
Venue: International Journal of Quality and Service Sciences
Year: 2019

The purpose of this study is to investigate the impact of service recovery dimensions on customer satisfaction and, subsequently, on customer loyalty in the context of the hotel industry.  A self administered questionnaire was distributed to 500 respondents who had the experiences of staying in the hotels in Malaysia. The structural equation modelling technique was used to study the relationship between the model and the developed hypotheses.  The findings revealed that service recovery dimensions are significantly related to customer satisfaction and have a positive relationship between customer satisfaction and customer loyalty.  As the main sector in the hospitality business, hotels play a vital role in the tourism industry. Therefore, the developments in tourism and hotels go hand in hand, as they are mutually dependent on each other. With significant yearly developments in the tourism industry and at a constant rate, hotel operators should reconsider their business strategies to achieve customer loyalty and sustain their businesses. In view of that, the findings of this study not only benchmarks better hotel services but also provides an improved understanding of service recovery that will effectively aid hotel operators in handling service failures; otherwise, customer dissatisfaction may occur if poor service recovery strategies are implemented.  The intense competition in the service industry has driven companies to place extra attention on service recovery so as to ensure continuous success. With a yearly significant development in the tourism industry at a constant rate, hotel providers (one of the major beneficiaries) are driven to reconsider their business strategies to achieve customer loyalty and sustain their business.
Investigation of Solution Behaviour of an Ionic Liquid in Diverse Cellosolves by Physicochemical Contrivance
Year: 2018

Solution behaviour prevailing in 1, 3 dimethylimidazoliummethylsulfate (IL) and some diverse industrially important alkoxy alcohols or cellosolves have been investigated by electrolytic conductivity, density viscosity (e) and FT IR spectroscopic investigation. The derived parameters such as the limiting molar conductivities (L0) association constants (KA) the distance of closest approach (R) etc. of the ions supplemented with conductance, density and viscosity have been evaluated using the Fuoss conductance equation. The quantitative values of molecular interactions from thermodynamic parameters have been discussed in terms of some non covalent interactions. Functional groups of the pure solvents and structural characteristics of ionic liquid in different solvents have been discussed and taken into contemplation for spectroscopic study.
An adaptive fuzzy predictive control of nonlinear processes based on Multi Kernel least squares support vector regression
Venue: Appl. Soft Comput.
Year: 2018

In this paper, an adaptive fuzzy Generalized Predictive Control (GPC) is proposed for discrete time nonlinear systems via Takagi Sugeno system based Multi Kernel Least Squares Support Vector Regression (TS LSSVR) The proposed adaptive TS LSSVR strategy is constructed using a multi kernel least squares support vector regression where the learning procedure of the proposed TS LSSVR is achieved in three steps: In the first step, which is an offline step, the antecedent parameters of the TS LSSVR are initialized using a fuzzy c means clustering algorithm. The second step, which is an online step, deals with the adaptation of the antecedent parameters which can be implemented using a back propagation algorithm. Finally, the last online step is to use the Fixed Budget Kernel Recursive Least Squares algorithm to obtain the consequent parameters. Furthermore, an adaptive generalized predictive control for nonlinear systems is introduced by integrating the proposed adaptive TS LSSVR into the generalized predictive controller (GPC) The reliability of the proposed adaptive TS LSSVR GPC controller is investigated by controlling two nonlinear systems: A surge tank and continuous stirred tank reactor (CSTR) systems. The proposed TS LSSVR GPC controller has demonstrated good results and efficiently controlled the nonlinear plants. Furthermore, the adaptive TS LSSVR GPC has the ability to deal with disturbances and variations in the nonlinear systems.
A martingale approach for fractional Brownian motions and related path dependent PDEs
Year: 2017

In this paper we study dynamic backward problems, with the computation of conditional expectations as a main objective, in a framework where the (forward) state process satisfies a Volterra type SDE, with fractional Brownian motion as a typical example. Such processes are neither Markov processes nor semimartingales, and most notably, they feature a certain time inconsistency which makes any direct application of Markovian ideas, such as flow properties, impossible without passing to a path dependent framework. Our main result is a functional It\{o} formula, extending the seminal work of Dupire \cite{Dupire} to our more general framework. In particular, unlike in \cite{Dupire} where one needs only to consider the stopped paths, here we need to concatenate the observed path up to the current time with a certain smooth observable curve derived from the distribution of the future paths. This new feature is due to the time inconsistency involved in this paper. We then derive the path dependent PDEs for the backward problems. Finally, an application to option pricing in a financial market with rough volatility is presented.
Variable Gain Gradient Descent based Reinforcement Learning for Robust Optimal Tracking Control of Uncertain Nonlinear System with Input Constraints
Year: 2019

In recent times, a variety of Reinforcement Learning (RL) algorithms have been proposed for optimal tracking problem of continuous time nonlinear systems with input constraints. Most of these algorithms are based on the notion of uniform ultimate boundedness (UUB) stability, in which normally higher learning rates are avoided in order to restrict oscillations in state error to smaller values. However, this comes at the cost of higher convergence time of critic neural network weights. This paper addresses that problem by proposing a novel tuning law containing a variable gain gradient descent for critic neural network that can adjust the learning rate based on Hamilton Jacobi Bellman (HJB) error and instantaneous rate of variation of Lyapunov function along augmented system trajectories. By allowing high learning rate the proposed variable gain gradient descent tuning law could improve the convergence time of critic neural network weights. Simultaneously, it also results in tighter residual set, on which trajectories of augmented system converge to, leading to smaller oscillations in state error. A tighter bound for UUB stability of the proposed update mechanism is proved. Numerical studies are then presented to validate the robust Reinforcement Learning control scheme in controlling a continuous time nonlinear system.
HUBUNGAN GAYA HIDUP HEDONIS DENGAN PERILAKU KONSUMTIF PADA MAHASISWI
Venue: Al Qalb Jurnal Psikologi Islam
Year: 2019

Setiap orang memiliki gaya hidup yang berbeda masing masing. Salah satunya adalah gaya hidup hedonis. Gaya hidup hedonis merupakan pola hidup yang cenderung mencari dan mengejar kesenangan sebagai tujuan hidupnya. Ketika seseorang menerapkan pola hidup seperti ini di dalam dirinya, maka akan menyebabkan seseorang tersebut menunjukkan perilaku konsumtif. Yaitu membelanjakan uangnya untuk suatu hal atau barang secara berlebihan di luar batas kebutuhannya. Tujuan penelitian ini adalah untuk mengetahui kategori dari gaya hidup hedonis pada mahasiswi, untuk mengetahui kategori dari perilaku konsumtif pada mahasiswi, dan untuk mengetahui hubungan gaya hidup hedonis dengan perilaku konsumtif mahasiswi.Metode yang digunakan dalam penelitian ini adalah metode kuantitatif dengan teknik analisis data yaitu analisis Pearson Correlation. Populasi dalam penelitian ini berjumlah 108 orang dengan sampel sebanyak 84 orang. Penarikan sampel pada penelitian ini adalah simple random sampling. Teknik pengumpulan data yang digunakan dalam penelitian ini adalah skala psikologi, yang berpedoman pada modifikasi skala Likert, yaitu skala gaya hidup hedonis dan skala perilaku konsumtif.Hasil penelitian menunjukkan bahwa mahasiswi semester IV Prodi Pendidikan Dokter Universitas Baiturrahmah Padang memiliki tingkat gaya hidup hedonis yang tinggi, mahasiswi semester IV Prodi Pendidikan Dokter Universitas Baiturrahmah Padang memiliki tingkat perilaku konsumtif yang tinggi, dan ada hubungan gaya hidup hedonis dengan perilaku konsumtif pada mahasiswi semester IV Prodi Pendidikan Dokter Universitas Baiturrahmah Padang.
DHA: Supervised Deep Learning to Hash with an Adaptive Loss Function
Venue: 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)
Year: 2019

Hashing, which refers to the binary embedding of high dimensional data, has been an effective solution for fast nearest neighbor retrieval in large scale databases due to its computational and storage efficiency. Recently, deep learning to hash has been attracting increasing attention since it has shown great potential in improving retrieval quality by leveraging the strengths of deep neural networks. In this paper, we consider the problem of supervised hashing and propose an effective model (i.e. DHA) which is able to generate compact and discriminative binary codes while preserving semantic similarities of original data with an adaptive loss function. The key idea is that we scale and shift the loss function to avoid the saturation of gradients during training, and simultaneously adjust the loss to adapt to different levels of similarities of data. We evaluate the proposed DHA on three widely used benchmarks, i.e. NUS WIDE, CIFAR 10, and MS COCO. The state of the art image retrieval performance clearly shows the effectiveness of our method in learning discriminative hash codes for nearest neighbor retrieval.
Factors Influencing the Adaptation Decisions to Impacts of Climate Change among the Maasai Pastoral Community in Narok County, Kenya
Year: 2019

Climate change has adverse effects on household food security and on poverty alleviation among pastoralists. This study used unique household level data from 415 pastoral households from three sub counties of Narok County in Kenya to identify the major determinants of their decision to select different community based adaptation strategies to impacts of climate change. The results from a logit model indicated that the household head characteristics (gender, education (secondary and university level) marital status, and the main occupation) socio economic and institutional factors (access to credit, access to water, and access to climate related information) were important in enhancing the adoption of the adaptation strategies to impacts of climate change. Therefore, to enhance the resilience of pastoral communities to impacts of climate change, policies that incorporate indigenous knowledge, promote community led adaptation, enhance effective and appropriate dissemination of climate related information at the local level and those that provide access to relevant institutions should be formulated. In addition, livestock off take schemes, and framework needs to be set through the establishment of effective and efficient livestock markets specifically in the pastoral areas in order to cushion pastoralist from deepening into food insecurity and poverty during the occurrences of extreme climate events.
Antibodies mediate intracellular immunity through tripartite motif containing 21 (TRIM21)
Venue: Proceedings of the National Academy of Sciences
Year: 2010

Antibodies provide effective antiviral immunity despite the fact that viruses escape into cells when they infect. Here we show that antibodies remain attached to viruses after cell infection and mediate an intracellular immune response that disables virions in the cytosol. We have discovered that cells possess a cytosolic IgG receptor, tripartite motif containing 21 (TRIM21) which binds to antibodies with a higher affinity than any other IgG receptor in the human body. TRIM21 rapidly recruits to incoming antibody bound virus and targets it to the proteasome via its E3 ubiquitin ligase activity. Proteasomal targeting leads to rapid degradation of virions in the cytosol before translation of virally encoded genes. Infection experiments demonstrate that at physiological antibody concentrations TRIM21 neutralizes viral infection. These results reveal an intracellular arm of adaptive immunity in which the protection mediated by antibodies does not end at the cell membrane but continues inside the cell to provide a last line of defense against infection.
What low back pain is and why we need to pay attention
Venue: The Lancet
Year: 2018

Low back pain is a very common symptom. It occurs in high income, middle income, and low income countries and all age groups from children to the elderly population. Globally, years lived with disability caused by low back pain increased by 54% between 1990 and 2015, mainly because of population increase and ageing, with the biggest increase seen in low income and middle income countries. Low back pain is now the leading cause of disability worldwide. For nearly all people with low back pain, it is not possible to identify a specific nociceptive cause. Only a small proportion of people have a well understood pathological cause eg, a vertebral fracture, malignancy, or infection. People with physically demanding jobs, physical and mental comorbidities, smokers, and obese individuals are at greatest risk of reporting low back pain. Disabling low back pain is over represented among people with low socioeconomic status. Most people with new episodes of low back pain recover quickly; however, recurrence is common and in a small proportion of people, low back pain becomes persistent and disabling. Initial high pain intensity, psychological distress, and accompanying pain at multiple body sites increases the risk of persistent disabling low back pain. Increasing evidence shows that central pain modulating mechanisms and pain cognitions have important roles in the development of persistent disabling low back pain. Cost, health care use, and disability from low back pain vary substantially between countries and are influenced by local culture and social systems, as well as by beliefs about cause and effect. Disability and costs attributed to low back pain are projected to increase in coming decades, in particular in low income and middle income countries, where health and other systems are often fragile and not equipped to cope with this growing burden. Intensified research efforts and global initiatives are clearly needed to address the burden of low back pain as a public health problem.
Toward a Phenomenology of Computational Thinking in STEM Education
Year: 2018

In this chapter, we argue for an epistemological shift from viewing coding and computational thinking as mastery over computational logic and symbolic forms to viewing them as a more complex form of experience. Rather than viewing computing as regurgitation and production of a set of axiomatic computational abstractions, we argue that computing and computational thinking should be viewed as discursive, perspectival, material, and embodied experiences, among others. These experiences include, but are not subsumed by, the use and production of computational abstractions. We illustrate what this paradigmatic shift toward a more phenomenological account of computing can mean for teaching and learning STEM in K 12 classrooms by presenting a critical review of the literature, as well as by presenting a review of several studies we have conducted in K 12 educational settings grounded in this perspective. Our analysis reveals several phenomenological approaches that can be useful for framing computational thinking in K 12 STEM classrooms.