Miracle-dz/UniFAR-FTUs huggingface dataset:
PERCEPTION ON THE "FUN OF FARAIDH (FoF)" GAME IN TEACHING & LEARNING OF THE INHERITANCE DISTRIBUTION SUBJECT

In 2016, statistics showed that RM60 billion worth of inheritance largely owned by Muslims was not being properly managed. This amount increased from RM52 billion in 2012, that is an increment of RM8 billion or 15 percent in 4 years. The main reason that caused this frozen property is the ignorance of the Muslim communities in faraidh knowledge. It has a detrimental impact on the economies of the Muslim communities especially those who earn low and moderate income. They have made their property lay idle and became frozen for a long period of time. Therefore, an understanding of the concept of Faraidh is beneficial in solving the above problem. This study was conducted to examine the perception of teaching staff at Universiti Teknologi Mara against the Fun of Faraidh game created by our innovation team in encouraging people to understand the distribution of inheritance in Faraidh system. A total of 21 people have been selected as the respondents and answered the questionnaires that have been given to obtain data after the implementation of the game. The results showed that more than 50% of the participants perceived Fun of Faraidh game has lots of advantages and is able to be used as a medium to comprehend the concept of faraidh. Hence, the game is perceivable as a new approach that can be an alternative tool in teaching and learning of faraidh.
Attention-based Learning for Missing Data Imputation in HoloClean

We study the problem of missing data imputation, a data validation task that machine learning researchers and practitioners confront regularly. We focus on mixed (discrete and continuous) data and introduce AimNet, an attention-based learning network for missing data imputation. AimNet utilizes a variation of the dot product attention mechanism to learn interpretable, structural properties of the mixed data distribution and relies on the learned structure to perform imputation. We perform an extensive experimental study over 14 real-world data sets to understand the role of attention and structure on data imputation. We find that the simple attention-based architecture of AimNet outperforms state-of-the-art baselines, such as ensemble tree models and deep learning architectures (e.g., generative adversarial networks), by up to 43% in accuracy on discrete values and up to 26.7% in normalized-RMS error on continuous values. A key finding of our study is that, by learning the structure of the underlying distribution, the attention mechanism can generalize better on systematically-missing data where imputation requires reasoning about functional relationships between attributes.
Brokered Trading in Fast Markets under Heterogeneous Private Values and Information

The paper develops a model of an order-driven market with very volatile motives for trade and a large number of (nearly) simultaneous limit and market order submissions. This corresponds to an electronic brokerage for very frequently traded securities such as highgrade bonds or FX. I consider small investors with a non-trivial distribution of private values for the traded asset as well as heterogeneous information about the parameters of this distribution across traders. The aim is to describe the price formation mechanism in this market. I study the properties of the mapping from the histogram of private asset values and private information endowments to the inside bid and ask price. Basic relationships between the limit order book, market sell and market buy order flow distributions, expected market order execution prices and the probabilities of a limit order execution at a given price, all as functions of private information, are derived. Traders are risk neutral as long as the transacted quantities are small, so that the limit and the market order decisions within one trading round do not feed back into private values. We formulate the equations that characterize the best ask and bid prices in this environment, as well as establish a number of properties of the equilibrium order book. JEL Classification: G12, G14, G19, G21, C72
Noise Contrastive Estimation

In prediction problems, we’re supposed to predict y ∈ Y from x ∈ X . We do this by assuming a joint distribution pXY from which we can sample correct pairs (x, y) and learning a score function s(x, y) ∈ R parameterized by θ such that it assigns a high score to a correct pair and a low score to an incorrect pair. To estimate such a score function, we often use the hinge loss (Appendix A) or the cross-entropy loss (Appendix B)
Mixing It Up: How Mixed Groups of Humans and Machines Modulate Conformity

This study examines to what extent mixed groups of computers and humans are able to produce conformity effects in human interaction partners. Previous studies reveal that nonhuman groups can induce conformity under certain circumstances, but it is unknown to what extent mixed groups of human and nonhuman agents are able to produce similar effects. It is also unknown how varying the number of human agents per group can affect conformity. Participants were assigned to one of five groups varying in their proportion of human to nonhuman agent composition and were asked to complete a social and analytical task with the assigned group. These task types were chosen to represent tasks which humans (i.e., social task) or computers (i.e., analytical task) may be perceived as having greater expertise in, as well as roughly approximating real-world tasks humans may complete. A mixed analysis of variance (ANOVA) revealed higher rates of conformity (i.e., percentage of time participants answered in line with their group on critical trials) with the group opinion for the analytical versus the social task. In addition, there was an impact of the ratio of human to nonhuman agents per group on conformity on the social task, with higher conformity with the group opinion as the number of humans in the group increased. No such effect was observed for the analytical task. The findings suggest that mixed groups produce different levels of conformity depending on group composition and task type. Designers of systems should be aware that group composition and task type may influence compliance and should design systems accordingly.
Digital Workerism: Technology, Platforms, and the Circulation of Workers’ Struggles

The use of digital technology has become a key part of contemporary debates on how work is changing, the future of work/ers, resistance, and organising. Workerism took up many of these questions in the context of the factory – particularly through the Italian Operaismo – connecting the experience of the workplace with a broader struggle against capitalism. However, there are many differences between those factories and the new digital workplaces in which many workers find themselves today. The methods of workers’ inquiry and the theories of class composition are a useful legacy from Operaismo, providing tools and a framework to make sense of and intervene within workers’ struggles today. However, these require sharpening and updating in a digital context. In this article, we discuss the challenges and opportunities for a “digital workerism”, understood as both a research and organising method. We use the case study of Uber to discuss how technology can be used against workers, as well as repurposed by them in various ways. By developing an analysis of the technical, social, and political re-composition taking place on the platform, we move beyond determinist readings of technology, to place different technologies within the social relations that are emerging. In particular, we draw attention to the new forms through which workers’ struggles can be circulated. Through this, we argue for a “digital workerism” that develops a critical understanding of how the workplace can become a key site for the struggles of digital/communicative socialism.
PhantomCache: Obfuscating Cache Conflicts with Localized Randomization

—Cache conﬂicts due to deterministic memory-to-cache mapping have long been exploited to leak sensitive information such as secret keys. While randomized mapping is fully investigated for L1 caches, it still remains unresolved about how to secure a much larger last-level cache (LLC). Recent solutions periodically change the mapping strategy to disrupt the crafting of conﬂicted addresses, which is a critical attack procedure to exploit cache conﬂicts. Remapping, however, increases both miss rate and access latency. We present PhantomCache for securing an LLC with remapping-free randomized mapping. We propose a localized randomization technique to bound randomized mapping of a memory address within only a limited number of cache sets. The small randomization space offers fast set search over an LLC in a memory access. The intrinsic randomness still sufﬁces to obfuscate conﬂicts and disrupt efﬁcient exploitation of con-ﬂicted addresses. We evaluate PhantomCache against an attacker exploring the state-of-the-art attack with linear-complexity. To secure an 8-bank 16 MB 16-way LLC, PhantomCache conﬁnes randomization space of an address within 8 sets and brings only 1.20% performance degradation on individual benchmarks, 0.50% performance degradation on mixed workloads, and 0.50% storage overhead per cache line, which are 2x and 9x more efﬁ-cient than the state-of-the-art solutions. Moreover, PhantomCache is solely an architectural solution and requires no software change.
Incidental Vocabulary Learning Through Movies

It is thought that in order to comprehend general conversation at the native-speaker level, it is necessary to know thousands of word families. Vocabulary learning is therefore a vital component to attaining proficiency in a language. Technological advances have greatly expanded the resources available to language students. In particular, learners increasingly have access to audio-visual, meaning-focused input, such as DVDs and streamed video material. Studies indicate that such materials can be used as linguistic input to facilitate incidental vocabulary learning, in the same way extensive reading (ER) uses graded readers have traditionally been used for the same purpose. The current study sought to measure the effect of watching a single movie in English, with English captions, on the ability of Japanese students to recall a selection of words taken from the movie script. The results revealed a significant increase in students’ ability to recall the words directly after watching the movie. From a list of 42 target words, the mean number of words recalled increased by 1.7 (4.05%) words after viewing. The result suggests that meaning-focused audio-visual input such as movies are a valuable supplementary resource for language learners, which can help provide a welcome boost to their rate of vocabulary acquisition.
Model Version 2 ( CESM 2 ) Configurations During the 2 20 th and 21 st Centuries

17 Model simulations from the Coupled Model Intercomparison Project Phase 6 (CMIP6) pro18 vide a useful framework for advancing our understanding of the polar transient climate 19 response. Here we report on the current and future states of Arctic sea ice in the Com20 munity Earth System Model version 2 (CESM2), the version of the CESM contributed to 21 CMIP6. We analyze changes in Arctic sea ice cover in two CESM2 configurations with dif22 fering atmospheric components: the CESM2-CAM6 and the CESM2-WACCM6. Over the 23 historical period, the CESM2-CAM6 winter ice thickness distribution is biased thin, which 24 leads to lower summer ice extent compared to the CESM2-WACCM6 and observations. In 25 both CESM2 configurations, the timing of first ice-free conditions is insensitive to the choice 26 of future CMIP6 emissions scenario. In fact, the probability of an ice-free Arctic summer 27 remains low only if global warming stays below 1.5◦C, which none of the CMIP6 scenarios 28 achieve. By the end of the 21 century, both CESM2 configurations exhibit an accelerated 29 decline in winter and spring ice extent under the high emissions scenario, a behavior that 30 had not been previously seen in CESM simulations. We find that the CESM2 simulates 31 less ocean heat loss during the fall months compared to its previous version, delaying sea 32 ice formation and leading to ice-free conditions for up to 8 months. Given that the CMIP6 33 high emissions scenario reaches higher levels of atmospheric CO2 by 2100 than its CMIP5 34 equivalent, this could explain why this winter ice loss was not previously simulated by the 35 CESM. 36 Plain Language Summary 37 We report on the current and future states of Arctic sea ice as simulated by one of the 38 latest large-scale climate models, the Community Earth System Model version 2 (CESM2). 39 The CESM2 model has two configurations that differ in their representation of atmospheric 40 processes: the CESM2-CAM6 and the CESM2-WACCM6. We find several differences in the 41 simulated Arctic sea ice cover between the two CESM2 configurations, as well as compared 42 to the previous generation of the CESM model. Over the historical period, the CESM243 CAM6 model simulates a winter ice cover that is too thin, which leads to lower summer 44 ice coverage compared to the CESM2-WACCM6 model and observations. In both CESM2 45 configurations, the probability of the Arctic becoming nearly ice free at the end of the 46 summer only remains low if global warming stays below 1.5◦C. In addition, the specific 47 year a first ice-free Arctic is reached is not sensitive to the amount of future greenhouse 48
Evaluation of Curing Process for Carbon-Epoxy Composites by Mechanical Characterization for Re-entry Vechicle Structure

The curing of carbon/epoxy laminates has resulted the volume fraction of 71.35%. It has been found that at reliability 0.90 the survival tensile strength and flexural strength of carbon/epoxy laminates are 721.753 MPa and 557.380 MPa respectively. The occurrence of drop in flexural modulus was probably due to the fracture of the 0° fibers of the surface lamina. The void fraction is 5.49%. The interlaminar shear strength was very responsive to the presence of these gas inclusions. The fibre controlled fracture was observed in the high volume fraction of carbon fibers in the carbon/epoxy laminates.
Sustainability Values of Students as Influences on the Image of a University Transitioning to Sustainability

The journey toward sustainability is a difficult process for a university given the complex requirements necessary for becoming sustainable. To implement sustainability initiatives effectively, therefore, it is important to obtain the support and commitment of university stakeholders. Having a good image as far as the school’s efforts at sustainability are concerned engages stakeholders and encourages that commitment. It is an important element of change as it provides evidence that the school is indeed serious in its activities. Yet is the perception of the school’s image influenced by the sustainability values of students? A survey of 798 college students at a private university in Metro Manila, Philippines was conducted to establish the relationship of the students’ sustainability values as these influenced their perception of the university’s image. Structural equation modeling (SEM) with the EQS program was used to examine links between student sustainability values, perceptions of the impact of school initiatives, and school image. Results indicate that the school’s image as a contributor to sustainability is influenced by the perception students have of the long-term impact of school initiatives and the importance they place on environmental management. Such results highlight the need for creating awareness about, as well as encouraging involvement with, sustainability initiatives among students, especially with activities that have long-term horizons. Creating such a positive image through the route established by this research would help provide focus and efficiencies in the university’s sustainability initiatives.
Dynamically Evolving, Large-scale

Searchius is a collaborative search engine that produces search results based solely on user provided web-related data. We discuss the architecture of this system and how it compares to current state-of-the-art search engines. We show that the global users’ preference over pages can be efﬁciently used as a metric of page quality, and that the inherent organization of the collected data can be used to discover related URLs. We also conduct an extensive experimental study, based on the web related data of 36483 users, to analyze the qualitative and quantitative characteristics of user collected URL collections, to investigate how well the users URL collections cover the web and discover the characteristics that affect the quality of the search re-sults under the proposed setting.
Reading Speed and Comprehension Enhancement in Hybrid Learning Delivery Mode

The main objective of this research is to find out whether rate-buildup reading, skimming, and scanning strategies applied in hybrid learning method help students boost their reading speed and comprehension. This research employed quasi-experimental design. 15 students were involved into experimental group and 15 were enrolled into control group. Students of experimental group were treated through hybrid learning delivery mode in which web-based portal accessible on www.muhaiminabdullah. com was hosted as reading portal while students of control group were assigned only to paper-based reading activities in face-to-face method of contents delivery. Both students of experimental group and students of control group successfully boost their reading speed and comprehension. It is implied that reading speed and comprehension are possible to be enhanced both in web-based reading portal and in face to face. The dispersion of standard deviation on posttest that tends to be high suggests that further researchers conduct the experiment in a more well-controlled design towards experimental group.
On the Number of Hyper m-ary Partitions

For any m > 2, we provide a formula for the number of hyper m-ary partitions of a number n in terms of the number of hyperbinary paritions of integers obtained from the base-m representation of n. By applying a known formula for hyperbinary partitions, we are able to give a formula for the number of hyper m-ary partitions of n in terms of the the base-m representation of n. Finally, we show how to use our result to provide alternate proofs of known results about hyper m-ary partitions.
RandomNet: Towards Fully Automatic Neural Architecture Design for Multimodal Learning

Almost all neural architecture search methods are evaluated in terms of performance (i.e. test accuracy) of the model structures that it finds. Should it be the only metric for a good autoML approach? To examine aspects beyond performance, we propose a set of criteria aimed at evaluating the core of autoML problem: the amount of human intervention required to deploy these methods into real world scenarios. Based on our proposed evaluation checklist, we study the effectiveness of a random search strategy for fully automated multimodal neural architecture search. Compared to traditional methods that rely on manually crafted feature extractors, our method selects each modality from a large search space with minimal human supervision. We show that our proposed random search strategy performs close to the state of the art on the AV-MNIST dataset while meeting the desirable characteristics for a fully automated design process.
Comparison of models for genetic analysis of traits from performance test of gilts using restricted maximum likelihood

The objectives of this research was to compare estimates of variance components using different animal models in order to determine whether simpler models produce estimates similar to those produced by more complex alternatives, and to determine the most suitable mixed model for estimating genetic parameters and genetic trends for traits in performance test of gilts using REML. Four mixed model was constructed: M1 (Random effect of Animal and fixed effects of farm, year, season and breed), M1 (M1 + regression influence of body weight at the end of performance test), M3 (M1 + regression influence of duration of performance test), and M4 (M2 + regression influence of body weight at the end of performance test). In examined mixed models, information criteria was lowest in model M4, which would be the most adequate model, while model M1 had largest information criteria, which suggested that this model was not suitable model for evaluation of genetic parameters. Strong negative genetic and phenotypic correlation is showed between MP and BFT1 and between MP and BFT2, while between AG and BFT1 and BFT2 established positive and negative genetic and phenotypic correlation. Between BFT1 and BFT2 was determined strong positive genetics and phenotypic correlation. Heritability traits in four models were at medium to high degree of heritability. The resulting genetic trends were different between models, with relatively high coefficients of determination (R2).
Demand Elasticities, Nominal Rigidities and Asset Prices Job Market Paper

I study heterogeneity in demand elasticities as a source of risk in asset pricing. I use high-frequency product price and quantity data from Amazon to overcome the classical endogeneity challenge and estimate demand elasticities for a large cross-section of firms. I find that firms facing more elastic demands are riskier and this is reflected in higher equilibrium average stock returns (6.2% annual return premium). I show that price stickiness contributes to these differences in risk: firms are slow to react to competitors’ price changes (compared to the predictions of a Calvo model). My empirical findings show the importance of having heterogeneous demand elasticities and degrees of price stickiness in macro-finance models. ∗Department of Finance, London Business School. I am particularly indebted to João Cocco, Francisco Gomes, Howard Kung and Anna Pavlova for their invaluable guidance and advice. I am also grateful to Simcha Barkai, Svetlana Bryzgalova, John Y. Campbell, Roberto Cram, Marco Grotteria, Nick Hirschey, Minsoo Kim, Thilo Kind, Christopher Lako (discussant), Sérgio Rebelo, Roberto Rigobon, Arkodipta Sarkar, Pasquale Schiraldi, Lukas Schmid (discussant), Henri Servaes, Varun Sharma, Dejanir Silva (discussant), Mikhail Tirskish, Vikrant Vig, Michael Weber, and seminar participants at the Society of Economic Dynamics, the ECB Young Economists Forum, Transatlantic Doctoral Conference, the QMUL Economics and Finance Workshop, the Lubrafin, the European Finance Association, the HEC PhD Workshop, for their insightful comments. This paper received the 2019 AQR Asset Management Institute Fellowship Award and the Best Paper award in the ECB Young Economists’ competition. I thank the Delloite Institute of Innovation and Entrepreneurship for financial support.
Attentional Role of Quota Implementation

This paper introduces a new role of quotas, e.g., labor market quotas: the attentional role. We study the effect of quota implementation on the attention allocation strategy of a rationally inattentive (RI) agent. Our main result is that a RI agent who is forced to fulfill a quota never hires the candidates without acquiring information about them, unlike an unrestricted RI agent who in some cases bases her decision on prior belief only. We also show that in our context quotas are equivalent to other types of affirmative policies such as subsidies and blind resume policy. We show how our results can be used to set a quota level that increases the expected value of the chosen candidate and also decreases statistical discrimination and discrimination in terms of how much attention is paid to each applicant. At the same time, quota implementation could be destructive if the social planner has imperfect information about the parameters of the model.