Miracle-dz/UniFAR-FTUs huggingface dataset:
A Mobile Agent Approach for Flexible Peer-to-Peer File Retrieval

Peer-to-peer (P2P) data sharing is one of valuable approaches for sharing data among people when they are belonging to different institutions. There are strong demands on both flexible, high-precision search and protection of privacy at peer-to-peer data retrievals. Especially, it is demanded for searching relevant files in P2P environment by using metadata while the terms in metadata that are used in such queries and annotations include some private information. In this paper, I present my current ongoing work on P2P-based semantic file sharing and retrieval mechanism that enables us to use private ontologies for flexible concept-oriented semantic searches without loss of privacy in processing semantic matchings among private metadata of files and the requested semantic queries. The private ontologies are formed on a certain reference ontology with differential ontologies for personalization. In our approach, users can manage and annotate their files with their own private ontologies. Reference ontologies are used to find out semantically relevant files for the given queries that include semantic relations among existing files and the requested files. Mobile agent approach is applied for the purpose to implement a system with less use of network bandwidth and also to code it into simple programs. A prototype system is implemented on the MiLog mobile agent programming platform. Discussions about potential advantages and issues on the approach are presented based on the prototype implementation.
The Effects of EITC Payment Expansion on Maternal Smoking

The Earned Income Tax Credit (EITC) is the largest anti-poverty program in the U.S. In 1993, the EITC benefit levels were changed significantly based on the number of children in the family such that families with two or more children experienced an exogenous expansion in their incomes. Using data from the National Longitudinal Survey of Youth 1979 cohort, we employ a triple differences plus Fixed-Effects framework to examine the effect of this change on the probability of smoking among low-educated mothers. We find that the probability of smoking for white and Hispanic low-educated mothers of two or more children decreased statistically significantly relative to those with only one child, and the results are robust to various specification tests. These results provide new evidence on the protective effect of income on health through changes in health behaviors, and therefore have important policy implications.
HPCMalHunter: Behavioral malware detection using hardware performance counters and singular value decomposition

Malicious programs, also known as malware, often use code obfuscation techniques to make static analysis more difficult and to evade signature-based detection. To resolve this problem, various behavioral detection techniques have been proposed that focus on the run-time behaviors of programs in order to dynamically detect malicious ones. Most of these techniques describe the run-time behavior of a program on the basis of its data flow and/or its system call traces. Recent work in behavioral malware detection has shown promise in using hardware performance counters (HPCs), which are a set of special-purpose registers built into modern processors providing detailed information about hardware and software events. In this paper, we pursue this line of research by presenting HPCMalHunter, a novel approach for real-time behavioral malware detection. HPCMalHunter uses HPCs to collect a set of event vectors from the beginning of a program's execution. It also uses the singular value decomposition (SVD) to reduce these event vectors and generate a behavioral vector for the program. By applying support vector machines (SVMs) to the feature vectors of different programs, it is able to identify malicious programs in real-time. Our results of experiments show that HPCMalHunter can detect malicious programs at the beginning of their execution with a high detection rate and a low false alarm rate.
Identifying Relevant Document Facets for Keyword-Based Search Queries

As structured documents with rich metadata (such as products, movies, etc.) become increasingly prevalent, searching those documents has become an important IR problem. Although advanced search interfaces are widely available, most users still prefer to use keyword-based queries to search those documents. Query keywords often imply some hidden restrictions on the desired documents, which can be represented as document facet-value pairs. To achieve high retrieval performance, it's important to be able to identify the relevant facet-value pairs hidden in a query. In this paper, we study the problem of identifying document facet-value pairs that are relevant to a keyword-based search query. We propose a machine learning approach and a set of useful features, and evaluate our approach using a movie data set from INEX.
Okul Liderliği Ölçeği (OLÖ) Geçerlik ve Güvenirlik Çalışması

Bu arastirmanin amaci, okul mudurlerine yonelik okul liderligi olcegi gelistirmektir. Olcek gelistirme calismasinda Brauckmann ve Pashiardis (2010) calismalarindaki liderlikle ilgili yargilar ile liderlik literaturu incelenerek farkli liderlik olceklerinde yer alan yargilardan yararlanilmis ve madde havuzu olusturulmustur. Olcegin gecerlik ve guvenirlik calismasi Sivas ili merkez ilcelerinde calisan birinci calisma grubu 270; ikinci calisma grubu 380 olmak uzere iki farkli orneklem uzerinden incelenmistir. Olcegin okul liderligini betimlemesi ve olcmesi acisindan kapsami ve icerigi acisindan incelenmesi icin birinci grup calisma grubu ile oncelikle acimlayici faktor analizi (AFA) yapilmistir. AFA sonuclarina gore olcegin uc faktorlu oldugu ve olcege iliskin aciklanan toplam varyansin %64.58 oldugu ortaya cikmistir. Ikinci calisma grubu uzerinden ise dogrulayici faktore analizi (DFA) yapilmistir. DFA sonucuna gore olcegin uyum iyiligi degerlerinin RMSEA=. 08; RMR =. 29; GFI =. 79; CFI = . 98; NFI =. 97; NNFI= . 98; AGFI= . 79 oldugu ve kabul edilir deger araliginda oldugu gorulmustur. Olcegin guvenirligi icin yapilan Cronbach Alfa ve Spearman Brown iki yari testi guvenirlik katsayilarinin, . 80’nin uzerinde degerlere sahip oldugu hesaplanmistir. Birinci calisma grubu uzerinden acimlanan olcegin ikinci calisma grubu uzerinden dogrulandigi anlasilmistir. Okul liderligi olcegi uc faktorlu 5’li likert olarak derecelendirilmis 31 maddelik olup gecerligi ve guvenirligi test edilmistir.
ANIMAL: A System for Supporting Multiple Roles in Algorithm Animation

Abstract Many algorithm animation tools have been developed over the last years. The users of such tools can be separated into four roles: the original algorithm programmer, developers of the animation tool, visualizers that generate the animation and end users viewing the animation. Most tools focus on providing features for only one or at most two of these roles. The ANIMAL system is designed to present valuable benefits for the last three roles. The principal research contributions of this work lie in dynamic extensibility, internationalization of GUI components and animation content, reversible animation display and flexible import and export facilities. We also present several core features of ANIMAL including dynamic reconfiguration, internationalization in both GUI and animations, display scaling, export facilities and full video player controls.
The Power of Integrated Abstraction for Data-Centric Human/Machine Computations

are recognized as important data sources in data-centric applications today. This paper discusses the potential of integrated abstraction of data-centric hu- man/machine computations, where data provided by people plays an important role. We show the potential by using a language named CyLog, our first attempt to develop such abstractions. In CyLog, the closed world assumption is in- terpreted in a broader world in which people are included as rational data sources, that behave rationally in given games. We argue that such abstractions give us opportunities to ap- propriately deal with computations not closed in machines.
Certified Interpolant Generation for EUF

Logical interpolants have found a wide array of applications in automated verification, including symbolic model checking and predicate abstraction. It is often critical to these applications that reported interpolants exhibit desired properties, correctness being first and foremost. In this paper, we introduce a method in which interpolants are computed by type inference within the trusted core of a proof checker. Interpolants produced this way from a proof of the joint unsatisfiability of two formulas are certified as correct by construction. We focus our attention to the quantifier-free theory of equality and uninterpreted functions (EUF) and present an interpolant generating proof calculus that can be encoded in the LFSC proof checking framework with limited reliance upon computational side conditions. Our experimental results show that our method generates certified interpolants with small overhead with respect to solving.
Mapping the political economy of education technology: A networks perspective

The field of education technology (edtech) has emerged as a complex, multimillion-dollar industry, with various hubs in the USA leading the boom. This exploratory article uses a networks perspective to reveal the power dynamics of investor firms in edtech. The analysis examines the current top venture capitalists and their edtech companies, based on primary funding relationships. The article begins with an explanation of how edtech emerged, an overview of the K-12 environment, and an analysis as to why edtech companies have become vital players in the education sector in the USA. This study highlights the most influential actors in the edtech political economy and their structures and interactions, and concludes with recommendations for future research. The investigation has involved examining the top investors and companies closely, alongside the political and economic motivations behind their investments.
Self-Care Ability and Self-Compassion : The Implication toward Life Satisfaction of the Elderly

The alteration and deterioration of physical and psychological function causes high levels in dependency of elderly age for asking help from others. Therefore, they need to optimize their self-care ability because it is expected to increase life satisfaction in elderly age. This study used self-compassion as a moderating variable that strengthens the influence of self-care ability to life satisfaction. The purpose of this study is to analyze the effect of self-care ability toward life satisfaction in elderly moderated by self-compassion. Researchers used quantitative correlation as a method in this current study. The study involved 215 elderly-age people who are members of Karang Wredha. So as to collect the data, Life Satisfaction Index-A, Exercises Self-Care Agency Scale and SelfCompassion Scale were employed as the instruments. Moderated Regression Analysis was used in order to analyze the taken data. The results have indicated that there are positive and significant impacts of self-care ability toward life satisfaction moderated by self-compassion.
IMAGE RETRIEVAL WITH VISUALLY PROMINENT FEATURES USING FUZZY SET THEORETIC EVALUATION

This paper proposes a new image retrieval scheme using visually significant features. Clusters of points around significant curvature regions (high, medium, weak type) are extracted to obtain a representative image. Illumination, viewpoint invariant color features are computed from those points for evaluating similarity between images. Relative importance of the features is evaluated using a fuzzy entropy based measure computed from relevant and irrelevant set of the retrieved images marked by the users. The performance of the system is tested using different set of examples from general purpose image database. Robustness of the system has also been shown when the images have undergone different transformations.
Perbandingan Model Discovery Learning Dengan Model Peer Teaching Terhadap Teknik Passing Bawah

Tujuan dari penelitian ini adalah untuk mengetahui tentang Perbandingan Model Pembelajaran Discovery Learning dan Model Pembelajaran Peer Teaching terhadap hasil belajar Teknik Dasar Passing Bawah dalam Bola Voli Pada Siswa Kelas XI di SMAN 1 Ciawigebang Kabupaten Kuningan. Metode yang digunakan dalam penelitian ini adalah metode eksperimen, dengan desain kelompok kontrol Pretest-Posttest, yang digunakan untuk mengetahui pengaruh dari suatu perlakuan terhadap subjek penelitian. Populasi dalam penelitian ini adalah siswa kelas XI SMA Negeri 1 Ciawigebang tahun ajaran 2016/1017 yang terdiri dari 9 kelas dengan jumlah 270 siswa. Setelah diketahui dari pembahasan diatas bahwa antara kedua model pembelajaran discovery learning dengan model pembelajaran peer teaching keduanya memiliki pengaruh yang baik, untuk mengetahui mana yang lebih baik dari keduanya maka dari itu dilakukan pengujian independent t-test, maka diperoleh nilai discovery learning dan peer teaching . Karena maka Ho ditolak. Hal ini membuktikan bahwa Model pembelajaran Peer Teaching lebih baik dibandingkan dengan model pembelajaran Discovery Learning terhadap Kemampuan Teknik Dasar Passing Bawah dalam Bola Voli pada Siswa Kelas XI di SMA Negeri 1 Ciawigebang.
NADP-Dependent Aldehyde Dehydrogenase from Archaeon Pyrobaculum sp.1860: Structural and Functional Features

We present the functional and structural characterization of the first archaeal thermostable NADP-dependent aldehyde dehydrogenase AlDHPyr1147. In vitro, AlDHPyr1147 catalyzes the irreversible oxidation of short aliphatic aldehydes at 60–85°С, and the affinity of AlDHPyr1147 to the NADP+ at 60°С is comparable to that for mesophilic analogues at 25°С. We determined the structures of the apo form of AlDHPyr1147 (3.04 Å resolution), three binary complexes with the coenzyme (1.90, 2.06, and 2.19 Å), and the ternary complex with the coenzyme and isobutyraldehyde as a substrate (2.66 Å). The nicotinamide moiety of the coenzyme is disordered in two binary complexes, while it is ordered in the ternary complex, as well as in the binary complex obtained after additional soaking with the substrate. AlDHPyr1147 structures demonstrate the strengthening of the dimeric contact (as compared with the analogues) and the concerted conformational flexibility of catalytic Cys287 and Glu253, as well as Leu254 and the nicotinamide moiety of the coenzyme. A comparison of the active sites of AlDHPyr1147 and dehydrogenases characterized earlier suggests that proton relay systems, which were previously proposed for dehydrogenases of this family, are blocked in AlDHPyr1147, and the proton release in the latter can occur through the substrate channel.
Scaling-up RAAMs

Modi cations to Recursive Auto-Associative Memory are presented, which allow it to store deeper and more complex data structures than previously reported. These modi cations include adding extra layers to the compressor and reconstructor networks, employing integer rather than real-valued representations, pre-conditioning the weights and pre-setting the representations to be compatible with them. The resulting system is tested on a data set of syntactic trees extracted from the Penn Treebank.
An overview of high-speed serial I/O trends, techniques and standards

The paper provides a brief overview of the basic building blocks within a high-speed serial transceiver, provides an outline of the major interconnect standards utilizing the highspeed serial I/O circuitry and gives the basics behind the design techniques required to design and implement a typical multi-GHz serial I/O device successfully. Several major design obstacles are presented, followed by a discussion of the potential design techniques that may be used to overcome such implementation issues. The paper covers two main design approaches: low swing differential signaling and multilevel signaling.
Distributed Optimal Relay Selection in Wireless Cooperative Networks With Finite-State Markov Channels

Relay selection is crucial in improving the performance of wireless cooperative networks. Most previous works for relay selection use the current observed channel conditions to make the relay-selection decision for the subsequent frame. However, this memoryless channel assumption is often not realistic given the time-varying nature of some mobile environments. In this paper, we consider finite-state Markov channels in the relay-selection problem. Moreover, we also incorporate adaptive modulation and coding, as well as residual relay energy in the relay-selection process. The objectives of the proposed scheme are to increase spectral efficiency, mitigate error propagation, and maximize the network lifetime. The formulation of the proposed relay-selection scheme is based on recent advances in stochastic control algorithms. The obtained relay-selection policy has an indexability property that dramatically reduces the computation and implementation complexity. In addition, there is no need for a centralized control point in the network, and relays can freely join and leave from the set of potential relays. Simulation results are presented to show the effectiveness of the proposed scheme.
Bird Species Identification from an Image

Identification of bird species is a challenging task often resulting in ambiguous labels. Even professional bird watchers sometimes disagree on the species given an image of a bird. It is a difficult problem that pushes the limits of the visual abilities for both humans and computers. Although different bird species share the same basic set of parts, different bird species can vary dramatically in shape and appearance. Intraclass variance is high due to variation in lighting and background and extreme variation in pose (e.g., flying birds, swimming birds, and perched birds that are partially occluded by branches). Our project aims to employ the power of machine learning to help amateur bird watchers identify bird species from the images they capture.
The European Central Bank's First Pillar Reassessed*

This paper studies the importance of money for inflation that is underlined by the first pillar of the European Central Bank’s policy concept. I focus on the quantity-theoretic link from core money growth to core inflation and embed it in a Phillips curve. The core components are approximated by the Hodrick-Prescott filter. It is shown that the data from the euro area fit the model well since the mid 1980s. A major result is that the money-to-inflation link has not been weakened by the start of EMU. I also discuss the merits of replacing the reference value by a range.
Improved read voltage margins with alternative topologies for memristor-based crossbar memories

Memories based on hysteretic resistive materials are expected to have superior properties such as nonvolatility, low power consumption, as well as very high capacity. Crossbar arrays are considered very attractive for future ultimately scaled memories. In this paper, the memristor-based passive crossbar geometry is studied and a set of different topological patterns, which introduce insulating junctions within the memory array, is presented. In the worst-case reading scenario the simulations revealed significantly improved sensed voltage margins (up to > 4×) which alleviate the rigorous requirement for large and highperformance CMOS sensing circuits in passive crossbar memory systems.
Bounded Memory and Biases in Information Processing ∗ Job Market Paper

This paper explores the connection between bounded memory and biases in information processing. An infinitely-lived decision maker receives a sequence of signals which provide partial information about the true “state of the world”; when this process terminates, which happens with probability η after each signal, he must make a decision whose payoff depends on the true state. We consider an agent with a bounded memory: he has a finite set of available memory states, and a memory process specifies which memory state to go to after new information is received (as a function of the current memory state). We show that with more than three memory states, the optimal memory process involves ignoring information with probability close to one, once the decision-maker is as convinced as his finite memory will allow. As a result, the behavior which is optimal in the long run creates many of the observed information processing biases in the short run. In particular, the agent appears to display a confirmatory bias (tendency to interpret information as supporting his current beliefs), and an overconfidence/underconfidence bias (tendency to read too much into ambiguous information, too little into highly diagnostic information). ∗I am indebted to Wolfgang Pesendorfer for extremely valuable suggestions at all stages of this project, and for the unlimited amount of time that he is willing to spend providing encouragement and advice. I also thank Faruk Gul for many helpful suggestions in the development of this paper, and Dilip Abreu and Ariel Rubinstein for helpful conversations. †Correspondence address: Department of Economics, 001 Fisher Hall, Princeton University, Princeton, NJ 08544. Telephone number: (609) 258-5409. E-mail: awilson@princeton.edu.
Education and Happiness: a Further Explanation to the Easterlin Paradox?

Previous empirical research has found a positive impact of education on happiness, on regional and worldwide scale. In this paper I analyze the effect of absolute income on human well-being by education level. Using data from the World Bank’s World Value Survey on more than 118,000 individuals I find that the higher the education level is, the less relevant the absolute income level (GDP per capita measured in PPP constant 2000 international USD) for self-declared life-satisfaction. Higher income makes everybody happier but, everything else being equal, the marginal utility of additional income is higher for less educated people. This might partly explain the Easterlin paradox. Although the GDP level has been constantly rising from the end of World War II onwards, the average life-satisfaction in Western Europe, Japan and the United States has remained almost constant. Furthermore, average happiness levels in rich and poor countries are not as different as GDP levels. Since the average education level has risen a lot over time and is much higher in advanced countries, this might contribute to explain why higher absolute income level has not implied higher life-satisfaction across countries and over time.
Who Should Save in a Roth 401(K)? (It’s Not Just About Tax Rates)

The advent of the Roth 401(k) significantly expanded opportunities for tax-preferred retirement saving, but at the same time it created much confusion for individual savers regarding whether to save in the form of pre-tax or Roth dollars. The financial community’s conventional wisdom is based on comparing current and future tax rates. We show how relying solely on the conventional wisdom can be wrong. We first show that comparing different saving strategies requires making an apples-to-apples comparison, which can be achieved by keeping take-home pay constant. An individual currently saving pre-tax can maintain the same take-home pay by switching to a lower amount of Roth saving. However, some important rules imposed by either 401(k) plans or the IRS encourage “tax illusion” by treating pre-tax and Roth dollars as if they were equivalent. First, moderate savers need to take care to understand how switching to Roth saving could lose them free money through employer matching contributions. Second, the IRS limit on annual 401(k) contributions means that aggressive savers who save Roth dollars can save more in a tax-advantaged way than those who save pre-tax dollars. For both of these groups, the conventional wisdom can be completely reversed under fairly normal circumstances.