Miracle-dz/UniFAR-FTUs huggingface dataset:
PENINGKATAN KETUNTASAN BELAJAR DAN SIKAP SOSIAL PESERTA DIDIK MELALUI PEMBERIAN REWARD UNTUK TUTOR SEBAYAPADA KONSEP GERAK HARMONIK SEDERHANA

Abstrak Penelitian ini bertujuan untuk mengetahui pengaruh pemberian reward kepada tutor sebaya terhadap peningkatan ketuntasan belajar dan sikap sosial peserta didik. Penelitian ini berbentuk eksperimen semu dengan Non-equivalentPretest-Posttest C ontrol Group Design. Pengambilan sampel dengan tehnik purposive sampling yaitu MIA 5 (kelas eksperimen) dan XI MIA 6 (kelas kontrol). Lima tutor dipilih dari setiap kelasdengan kriteria yang sudah ditentukan. Data dikumpulkan dengan menggunakan uji pilihan ganda dengan 19 item yang sebelumnya divalidasi oleh ahli serta diuji coba, sedangkan lembar observasi sikap sosial peserta didik hanya divalidasi pakar, untuk pengujian hipotesis menggunakan uji-t. Berdasarkan analisis data diperoleh skor rata-rata ketuntasan belajar peserta didik kelas eksperimen dan kontrol yaitu 75 dan 67dengan N-gain yakni 0,62 dan 0,50, dan skor rata-rata sikap sosial diperoleh 3,48 dan 2,32 untuk tutor serta 3,23 dan 2,23 untuk peserta didik.Hasil penelitian didapatkan nilai N-gain t hitung sebesar -4,608 dan t tabel sebesar 2,000 atau t hitung > t tabel , menunjukkan terdapat perbedaan signifikan ketuntasan belajar dan sikap sosial peserta didik yang diajarkan antara strategi pembelajaran tutor diberikan reward dan tutor tanpa pemberian reward. Ini berarti strategi pembelajaran tutor sebaya dengan pemberian reward mampu meningkatkan ketuntasan belajar dan sikap sosial peserta didik kelas XI MIA SMA Negeri 2 Bireuen. Kata kunci : reward , tutor sebaya, ketuntasan belajar, sikap sosial
High Performance Clustering for Web Person Name Disambiguation Using Topic Capturing

ABSTRACT Searching for named entities is a common task on the web. Among different named entities, person names are among the most frequently searched terms. However, many people can share the same name hard to find as they are being returned as very low ranked files and the current search engines are not designed to identify a specific entity, or that would normally be missed.a namesake. One possible solution is to identify a namesake through clustering webpages for different namesakes. In this paper, we propose a clustering algorithm which makes use of topic related information to improve clustering. The system is trained on the WePS2 dataset and tested on both the WePS1 and WePS2 dataset. Experimental results show that our system outperforms all the other systems in the WePS workshops using B-Cubed and Purity based measures. And the performance is also consistent and robust on different datasets. Most important of all, the algorithm is very efficient for web persons disambiguation because it only needs to use data already indexed in search engines. In other words, only local data is used as feature data to avoid query induced web search.
DCSPARK: Virtualizing spark using Docker containers

As MapReduce has become a popular model for large-scale data procession in recent years, companies and researchers take advantage of this model to solve their problems. The applications may run on the same MapReduce cluster, with their own system-wide configure settings and library dependencies, respectively. Sometimes, their configure settings and library dependencies are conflicted with each other. How to ensure these applications to run together correctly without mutual interference and achieve high resources utilization gives a challenge to the researchers. In this paper, we propose DCSpark, a framework that leverages the power of Docker containers that allows users to run Spark applications which have conflicting configurations and library dependencies in one physical cluster. In addition, it's presented an implementation of our framework called DCM which is aimed at managing the physical cluster, processing scheduling problem and building the container-based Spark cluster images automatically according to the dependence environment of the applications. Our experimental evaluation shows that DCSpark introduces negligible overhead for CPU and memory performance compared with the native Spark cluster.
Reranking for Sentence Boundary Detection in Conversational Speech

We present a reranking approach to sentence-like unit (SU) boundary detection, one of the EARS metadata extraction tasks. Techniques for generating relatively small n-best lists with high oracle accuracy are presented. For each candidate, features are derived from a range of information sources, including the output of a number of parsers. Our approach yields significant improvements over the best performing system from the NIST RT-04F community evaluation
Coalition Formation in Games Without Synergies

This paper establishes sufficient conditions for the existence of a stable coalition structure in the "coalition unanimity" game of coalition formation, first defined by Hart and Kurz (1983) and more recently studied by Yi (1997, 2003). Our conditions are defined on the strategic form game used to derive the payoffs of the game of coalition formation. We show that if no synergies are generated by the formation of coalitions, a stable coalition structure always exists provided that players are symmetric and either the game exhibits strategic complementarity or, if strategies are substitutes, the best reply functions are contractions.
Antifungal Activity of Essential Oils from Indian Medicinal Plants Against Human Pathogenic Aspergillus fumigatus and A. niger

Oils extracted from fifteen medicinal plants were screened for their activity against A. fumigatus and A. niger by disc diffusion method. Minimum inhibitory concentrations (MICs) of oils (%v/v) against Aspergillus fumigatus and Aspergillus niger done by agar dilution method and minimum inhibitory concentration (MIC) and minimum cidal concentration (MCCs) data (%v/v) obtained by the broth micro dilution method. The results showed that the maximum antimycotic activity was demonstrated by oils of Cymbopogon martini, Eucalyptus globulus and Cinnamomum zylenicum as compared to control, followed by Cymbopogon citratus which showed activity similar to control (miconazole nitrate). The oils of Mentha spicata, Azadirachta indica, Eugenia caryophyllata, Withania somnifera and Zingiber officinale exhibited moderate activity. The oils of Cuminum cyminum, Allium sativum, Ocimum sanctum, Trachyspermum copticum, Foeniculum vulgare and Elettaria cardamomum demonstrated comparatively low activity against A. niger and A. fumigatus as compared to control. Mixed oils showed maximum activity as compared to standard. These results support the plant oils can be used to cure mycotic infections and plant oils may have role as pharmaceutical and preservatives.
An entropy inspired measure for evaluating ontology modularization

Ontology modularization has received growing interest from the research community lately, since it supports tasks such as ontology design/reuse and knowledge selection and integration. Most of the research efforts have concentrated on approaches to extract modules, or generate partitions from an ontology. However these approaches are influenced by different definitions of ontology modularization and thus tend to vary w.r. t. the concepts and properties in the ontology that should define the module, and on the characteristics that modules should exhibit, which often depend on the task for which the modularization process is performed. This diversity of approaches makes the comparative evaluation of the output of different modularization processes hard to perform. In this paper, we propose an entropy inspired measure for modularization, Integrated Ontology Entropy, that approximates the information content of modules, and hence provides a profile for the module generated. This measure is independent of the modularization technique used, and is calculated as a function of the number of edges connecting the named concepts in the ontology, when a graph representation of the ontology is utilized. In the paper we apply this measure to different modularization techniques and we empirically show how the measure captures different characteristics of modules, such as the degree of redundancy and the level of connectedness.
Affective and cognitive religiosity: Influences on consumer reactance and self‐control

College of Business, Department of Management and Marketing, University of Wyoming, 1000 E. University Ave., Dept. 3275, Laramie, WY 82071, USA Correspondence Elizabeth A. Minton, Assistant Professor, College of Business, Department of Management and Marketing University of Wyoming 1000 E. University Ave., Dept. 3275 Laramie, WY 82071, USA. Email: eminton@uwyo.edu Funding information University of Wyoming
Can Anybody Help?: Mitigating IS Development Project Risk with User Involvement

In this paper we aim to gain insight into the relationship between user participation modes and project risk factors, and then we construct a model that can be used to determine how user participation can be successfully applied in ISD projects with a given set of risk factors. We perform an in-depth literature review, which aims to clarify the concept of user participation as part of risk management. We then report on the results of a case study in Cap Gemini where we conduct an exploratory research of the application of user participation in practice. For this exploratory research, a quantitative and qualitative research method was designed in the form of a survey and interviews. Though the results from our case study we gain insight into the relationship between user participation and IS project risk and also determine how user participation can be used to mitigate such risk.
The social construction of dyslexia in UK higher education

This thesis explores dyslexia support in higher education. The research is focussed primarily upon investigating dyslexia as a social construct, and the pedagogical strategies that are employed as part of a specialist intervention. Given the increasing numbers of students either identified with dyslexia before they enrol at university, or during their courses, the background to this thesis is the assumption amongst policy makers and funding bodies that dyslexia support, specifically that which is funded through Disabled Students Allowance (DSA), is specialised and distinct. Investigating the premise that support may be specialist, this research has drawn its findings from analysing the shared understandings of dyslexia, and the social processes that contribute to how specialists respond to it. The findings reveal that how dyslexia specialists have arrived at their understanding of the conditions is as much based on social circumstances and shared assumptions, as it is anything revealed in primary research. Within higher education in particular dyslexia is constructed through social processes that include psychological testing of students, assessing their needs to allocate funding, and discursively referring to dyslexia using medicalised and disabling terminology. The research concludes that the actual pedagogical interventions used by specialist tutors, and suggested in specialist literature, is not easily justified as specialist when compared against similar strategies used to develop students’ study skills.
The kinematics of directional control in the fast start of zebrafish larvae

ABSTRACT Larval fish use the ‘fast start’ escape response to rapidly evade the strike of a predator with a three-dimensional (3D) maneuver. Although this behavior is essential for the survival of fishes, it is not clear how its motion is controlled by the motor system of a larval fish. As a basis for understanding this control, we measured the high-speed kinematics of the body of zebrafish (Danio rerio) larvae when executing the fast start in a variety of directions. We found that the angular excursion in the lateral direction is correlated with the yaw angle in the initial stage of bending (stage 1). In this way, larvae moved in a manner similar to that reported for adult fish. However, larvae also have the ability to control the elevation of a fast start. We found that escapes directed downwards or upwards were achieved by pitching the body throughout the stages of the fast start. Changes in the pitching angle in each stage were significantly correlated with the elevation angle of the trajectory. Therefore, as a larva performs rapid oscillations in yaw that contribute to undulatory motion, the elevation of an escape is generated by more gradual and sustained changes in pitch. These observations are consistent with a model of motor control where elevation is directed through the differential activation of the epaxial and hypaxial musculature. This 3D motion could serve to enhance evasiveness by varying elevation without slowing the escape from a predator. Summary: The 3D direction of an escape response by a larval zebrafish is correlated with the degree of body rotation in yaw and pitch.
Financial Market Integration and the Value of Global Diversification: Evidence from US Acquirers in Cross-Border Mergers and Acquisitions

In contrast to the previously documented cross-border discount, we find that there is positive cross-border effect for US acquirers during late 1990s and early 2000s. This is especially particular the case for those that acquire/merge with targets from segmented financial markets where acquirers experience significantly higher positive abnormal returns than those that acquire targets from integrated financial markets. Furthermore, firms acquiring segmented-market targets are also characterized by significantly higher post-merger operating performance improvement. The results indicate that the observed positive cross-border effect is mainly due to the increase in the number of transactions involving targets from segmented markets, in which the average firm experience significant financial constraints. We contend that value is created by a combination of firms with different financial market integration status, in which funds are provided to high cost firms. The finding that the value creation is even higher within the group of acquirers with a lower cost of capital provides additional support for our conjecture.
Count Models of Social Networks in Finance

Social networks are thought to be important for the investment and performance of mutual fund managers. We propose a measure of whether a manager is part of a network using only data on the distribution of the number of stocks headquartered in a given city that are held by managers. For some cities, the count distribution is roughly Poisson. However, for a significant fraction of cities, the count distribution is highly overdispersed Poisson --- where most managers have a couple of picks but a few managers have many picks. We show that the degree of overdispersion is a theoretically well-motivated measure of network influence and that managers with concentrated stock picks in a city are likely to be part of a network in that city. These managers indeed significantly outperform other managers by around 1.6% per annum.
Education Abroad and Domestic Cultural Immersion: A Comparative Study of Cultural Competence Among Teacher Candidates

ABSTRACT As the demographics of the United States continue to shift, American classrooms reflect the richness of cultural diversity and the vibrancy of immigrant populations. Education abroad programs provide opportunities for preservice teachers to develop their cultural competence, required for effectively teaching children from a range of cultural backgrounds. Given the financial demands of study abroad programs, researchers have also examined domestic cultural immersion experiences. There is a lack of research that compares education abroad with domestic cultural immersion. This study contributes to the literature by comparing preservice teachers' responses to two cultural immersion experiences that are closely aligned both in content and in pedagogy, one in Israel and the other in a domestic setting.
14 Virtual Reality Exposure Therapy vs. Imagery Desensitization Therapy in the Treatment of Flying Phobia

This study examined the value of virtual reality graded exposure therapy (VRGET) compared to standard graded exposure therapy using imagery alone for patients with flying phobia. Thirty subjects were randomized into either VRGET with physiological feedback of skin resistance, peripheral skin temperature, heart rate, and respiration; VRGET with no physiological feedback, or imagery conditions. Patients in all conditions were first taught to relax (for two sessions) and then exposed in six subsequent sessions to flying stimuli (either through a virtual airplane with visual and somatic stimuli, or through producing mental images). Results showed that subjects in all three conditions were equally physiologically and subjectively aroused throughout the exposure series. However while only 20% of imagery patients flew after 8 weeks of therapy, 80% of VR patients receiving no physiological feedback and 100% of VR patients receiving physiological feedback were able to fly without using medications (p<.001). This is the first study to compare the benefit of virtual reality graded exposure therapy to graded exposure using imagery alone.
A comparison of fuzzy ARTMAP and Gaussian ARTMAP neural networks for incremental learning

Automatic pattern classifiers that allow for incremental learning can adapt internal class models efficiently in response to new information, without having to retrain from the start using all the cumulative training data. In this paper, the performance of two such classifiers - the fuzzy ARTMAP and Gaussian ARTMAP neural networks - are characterize and compared for supervised incremental learning in environments where class distributions are fixed. Their potential for incremental learning of new blocks of training data, after previously been trained, is assessed in terms of generalization error and resource requirements, for several synthetic pattern recognition problems. The advantages and drawbacks of these architectures are discussed for incremental learning with different data block sizes and data set structures. Overall results indicate that Gaussian ARTMAP is the more suitable for incremental learning as it usually provides an error rate that is comparable to that of batch learning for the data sets, and for a wide range of training block sizes. The better performance is a result of the representation of categories as Gaussian distributions, and of using category-specific learning rate that decreases during the training process. With all the data sets, the error rate obtained by training through incremental learning is usually significantly higher than through batch learning for fuzzy ARTMAP. Training fuzzy ARTMAP and Gaussian ARTMAP through incremental learning often requires fewer training epochs to converge, and leads to more compact networks.
Localization-Free Detection of Replica Node Attacks in Wireless Sensor Networks Using Similarity Estimation with Group Deployment Knowledge

Due to the unattended nature and poor security guarantee of the wireless sensor networks (WSNs), adversaries can easily make replicas of compromised nodes, and place them throughout the network to launch various types of attacks. Such an attack is dangerous because it enables the adversaries to control large numbers of nodes and extend the damage of attacks to most of the network with quite limited cost. To stop the node replica attack, we propose a location similarity-based detection scheme using deployment knowledge. Compared with prior solutions, our scheme provides extra functionalities that prevent replicas from generating false location claims without deploying resource-consuming localization techniques on the resource-constraint sensor nodes. We evaluate the security performance of our proposal under different attack strategies through heuristic analysis, and show that our scheme achieves secure and robust replica detection by increasing the cost of node replication. Additionally, we evaluate the impact of network environment on the proposed scheme through theoretic analysis and simulation experiments, and indicate that our scheme achieves effectiveness and efficiency with substantially lower communication, computational, and storage overhead than prior works under different situations and attack strategies.
Evolving Quantum Oracles with Hybrid Quantum-inspired Evolutionary Algorithm

Quantum oracles play key roles in the studies of quantum computation and quantum information. But implementing quantum oracles efficiently with universal quantum gates is a hard work. Motivated by genetic programming, this paper proposes a novel approach to evolve quantum oracles with a hybrid quantum-inspired evolutionary algorithm. The approach codes quantum circuits with numerical values and combines the cost and correctness of quantum circuits into the fitness function. To speed up the calculation of matrix multiplication in the evaluation of individuals, a fast algorithm of matrix multiplication with Kronecker product is also presented. The experiments show the validity and the effects of some parameters of the presented approach. And some characteristics of the novel approach are discussed too.
PENGEMBANGAN MEDIA PEMBELAJARAN MOBILE LEARNING BERBASIS ANDROID MATA PELAJARAN IPA UNTUK SISWA SMP

This study aims to (1) produce learning media based on android mobile learning (2) to know the level of feasibility of learning media according to material experts, media experts, and users, (3) to know the effectiveness of learning media to improve the learning outcomes of junior high school students. This development study follows the steps developed by Alessi and Trollip consisting of three stages: planning, designing and development. Initial product validated by media expert and material expert then revised. The next stage is a small group beta test carried out to six prospective users, and tested to 32 users. Furthermore sumative test against 32 students. The results showed that (1) android-based mobile learning products packaged in android package format (apk) using helios eclips software. (2) mobile learning product is considered feasible as a learning media based on the assessment of media experts 3,8 and material experts 4.3 with the category of "very good". (3) the effectiveness of the product is evidenced by the increase of learning outcomes to reach the average score of pretest score 65.46 and posttest of 79.53
What Does Emotion Have to Do with Learning? Everything!

“When educators fail to appreciate the importance of students’ emotions, they fail to appreciate a critical force in students’ learning. One could argue, in fact, that they fail to appreciate the very reason that students learn at all. ” (Immordino-Yang 2016, p.40) In the April 2017 JFSE editorial, we began exploring the emotional dimensions of learning. I have continued that expedition by discussing the topic with a wide variety of people, including my colleagues, the Illinois Center for Innovations in Teaching and Learning personnel, my husband, my children, my friends, and my children’s teachers. I also have continued the journey by deep readingi the book “Emotions, Learning, and the Brain” by Mary Helen Immordino-Yang (2016). My deep reading of the first few chapters, which are focused on why and how emotions are integral to learning, caused me to grow in appreciation of the profound and impactful relationship that exists between emotion and cognition. In turn, it also strengthened my resolve to discover ways that I could incorporate what I was learning about emotion and cognition into my pedagogical practices. Thus, the purpose of this editorial is to further explain and convince you, the readers, of the critical connection between emotion and deep, meaningful learning. Once convinced, I believe you won’t be able to help it; you will be driven, like I am, to learn more about how to practically employ emotion to facilitate cognition in your classroom (or workplace, or boardroom, or team, and so on).