Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrated Information System Teaching Plan in College Using FAST Method and Twitter Bootstrap

Abstract Teaching plan is one of the obligations that must be made by lecturer before conducting any lecture because teaching plan will be used by lecturer as a reference in determining Learning Outcomes (LO) and providing recovery materials in each semester. Unfortunately, there are still many existing teaching plans in College which are still manually developed. Thus, they may undermine head courses and Institute of Educational Development Study and Majors to perform learning monitoring and evaluation in the department.This research developes a system application which facilitates lecturer in managing teaching plan recovery and facilitates the Institute of Educational Development Study and Majors in evaluating the learning effectiveness, the suitability of the teaching journal and the achievement of Learning Outcomes. The system is developed using FAST method (Framework for the Application of System Thinking) and designed using a responsive Twitter Bootstrap template. The information generated system can also be used to support the cccreditation of Program Study. The testing process in this system uses blackbox testing to check the stability of the deployed system. The result of the test shows that all functions in the system runs perfectly, and the lecturers are more easily managing the Teaching plan, and the head of the Department can evaluate the suitability of the Teaching plan with teaching journal.
Cross Domain Residual Transfer Learning for Person Re-Identification

This paper presents a novel way to transfer model weights from one domain to another using residual learning framework instead of direct fine-tuning. It also argues for hybrid models that use learned (deep) features and statistical metric learning for multi-shot person re-identification when training sets are small. This is in contrast to popular end-to-end neural network based models or models that use hand-crafted features with adaptive matching models (neural nets or statistical metrics). Our experiments demonstrate that a hybrid model with residual transfer learning can yield significantly better re-identification performance than an end-to-end model when training set is small. On iLIDS-VID and PRID datasets, we achieve rank-1 recognition rates of 89.8% and 95%, respectively, which is a significant improvement over state-of-the-art.
Pengaruh Kualitas Wesbite Terhadap Kinerja Bisnis, Studi Kasus Website Travel

Situs web adalah sarana bertukar dan berbagi informasi antar pengguna. Situs web menyampaikan informasi dalam berbagai jenis, bahasa, dan bentuk serta kombinasi teks, gambar, suara, dan video yang dimaksudkan untuk menginformasikan, membujuk, menjual, dan memberikan perspektif atau bahkan mengubah sikap atau keyakinan. Usability website travel merupakan bagian dari kualitas website yang erat kaitannya dengan kualitas pelayanan yang berdampak pada kepuasan pelanggan. Untuk mengetahui kualitas website, dapat dilakukan ppengukuran. Teori utama yang akan digunakan dalam penelitian ini adalah teori WebQual. Tahap pertama adalah identifikasi faktor-faktor yang mempengaruhi kualitas website dengan menggunakan domain WebQual dan beberapa domain lainnya yang dihasilkan dari studi literatur. Domain tersebut adalah Kegunaan, Kualitas Informasi, Interaksi Layanan, Fungsionalitas Situs Web, dan Hubungan Pelanggan. Tujuan dari penelitian adalah mengidentifikasi faktor-faktor yang menjadi prioritas dalam mengukur kualitas website travel. Kemudian, menganalisis kesenjangan antara mengukur kualitas website melalui survei pengguna dengan mengukur kualitas website melalui evaluasi berbasis pakar. Terakhir adalah menganalisis pengaruh kualitas website terhadap kinerja bisnis e-travel. Pendekatan yang digunakan adalah metode Analytic Hierarchy Process (AHP). Data diproses menggunakan metode AHP dan menghasilkan bobot lokal dan global untuk setiap domain dan parameter pendukungnya. Hasilnya adalah parameter yang berada pada domain Usability mendominasi dengan urutan Positive Experience (Global Weight: 0.071) pada posisi pertama, parameter Easy To Use (Global Weight: 0.067) dan diketahui bahwa kualitas website berbanding lurus dengan kinerja bisnis. Hal ini dibuktikan dengan website yang menempati posisi pertama dari segi kualitas website sama dengan website yang menempati posisi pertama dari segi kinerja bisnis.
Christians and the Codex: Generic Materiality and Early Gospel Traditions

Abstract:Why did Christians in the second through fifth centuries overwhelmingly utilize the codex format while other contemporaries used the scroll for literary texts almost exclusively? We offer the concept of "generic materiality," which connects genre with material format. The early readers and users of the Gospel according to Mark in particular, and other gospels more generally, often described and treated them not as "books" with authors but as ὑπομνήματα or commentarii. Notebooks like ὑπομνήματα are typically described as circulating in tabulae, or the codex form. The prevalence of the codex form among second- through fifth-century biblical manuscripts derives in large part from durable generic expectations.
Factors that Influence the Adoption of Postgraduate Online Courses

A research about factors that lead students to choose online courses, as well as the acceptance of these courses, can provide very relevant information for higher education institutions’ decision makers to amend these offers to students’ interests and needs. An investigation through questionnaire was developed involving students who attended online post-graduate courses. It was intended to know which factors affect students' decision to opt for postgraduate online courses. A model, based on the TAM (Technology Acceptance Model), was tested to find out what factors determine the intention to use online learning. The results shows that most respondents favour online courses and that their decision, when choosing this type of course, is mainly influenced by time management flexibility, avoiding going to school and the course curriculum interest. The test of the model, with structural equations, shows that attitude regarding online courses and perceived usefulness are factors that predict the intention to use. It was also concluded that the perceived ease of use induces a direct and indirect effect on the intention to use. The most significant results are consistent with published studies and can help the higher education institutions to define offer and communication strategies to reach a greater number of candidates for online learning.
Integrating Technology into ESP Classes: Use of Student Response System in English for Specific Purposes Instruction.

This paper presented the results of an experimental study investigating the impact of clicker use through a smart phone application called Kahoot ! Despite positive results of clicker use in the existing General English literature, the impact of clicker use has not been examined in the field of ESP. To address this issue, this study investigated the effectiveness of clickers by comparing pre-test and post-test scores of a control and an experimental group and the scores of male and female participants in the experimental group. The results of a 10-week implementation of clicker use with the students of tourism and hospitality department in the experimental group indicated that while post-test scores were significantly higher for the experimental group than for the control group, there was not a statistically significant difference between the post-test scores of male and female participants in the experimental group. Implications for teaching ESP with the help of technology and suggestions for further research were also provided.
Evaluation of the Single Keybit Template Attack

Side Channel leakage is a serious threat to secure devices. Cryptographic information extraction is possible after examining any one of the various side channels, including electromagnetic. This work contributes a new method to achieve such a purpose. The Single Keybit Template Attack (SKTA) is introduced as a means to extract encryption keys from embedded processors and other integrated circuit devices performing DES encryptions by passively monitoring and exploiting unintentional RF emissions. Key extraction is accomplished by creating two templates for each bit value of the key based on instantaneous amplitude responses as a device executes DES operations. The resultant templates are input to a Maximum Likelihood processor for subsequent template discrimination with RF emissions captured from a target device. Plaintext and ciphertext are not necessary for SKTA to function. Using 8-bit microcontroller devices and experimentally collected side channel signals, key extraction is possible after examination of approximately 300 RF emission traces. After consideration of SKTA’s capabilities, embedded processors using DES to process sensitive data warrants reconsideration.
ANALYTICAL STUDY OF MACHINE TRANSLATING SYSTEM IN NLP

Automatic methods of measuring MT performance give us the ability to evaluate various features and present objective results without worrying about agreement rates of humans [1] . The problem of human agreement has been shifted to the set of references that are developed for a set of documents and each test system can then be evaluated objectively since the set of references are common to all systems [2]
Wave skeletonization algorithm for raster images

This article covers a wave skeletonization algorithm for raster images. It contains diagrams of algorithms for primary graph building and separating wave generation into wavelets. It is proposed to store the graph’s structure in nested form to save memory and make it easier to modify. Deming orthogonal regression is proposed for primary graph optimization as part of successive approximations method.
Nietzsche's intuitions

ABSTRACT This essay examines a particular rhetorical strategy Nietzsche uses to supply prima facie epistemic justification: appeals to intuition. I first investigate what Nietzsche thinks intuitions are, given that he never uses the term ‘intuition’ as we do in contemporary philosophy. I then examine how Nietzsche can simultaneously endorse naturalism and intuitive appeals. I finish by looking at why and how Nietzsche uses appeals to intuition to further his philosophical agenda. Answering these questions should provide a new and deeper understanding of how Nietzsche does philosophy.
OQAM/FBMC for future wireless communications : principles, technologies and applications

OQAM/FBMC for Future Wireless Communications: Principles, Technologies and Applications? introduces the concepts and key technologies of OQAM/FBMC, which has been regarded as the potential physical layer technique in future wireless communication systems. It comprises 10 chapters that provide an overview of wireless communications, introduce wireless channels, single carrier and multicarrier modulations, and three types of FBMC systems, also comparing OQAM/FBMC with OFDM. Other chapters introduce the OQAM/FBMC communication system model, the FFT implementation, CP insertion, PSD analysis, prototype filter optimization, joint PAPR reduction and sidelobe suppression, overhead reduction with virtual symbols, time and frequency domain channel estimations, block-wise SFBC for MIMO OQAM/FBMC, and much more.Provides a comprehensive guide to most major OQAM/FBMC techniquesIncludes a detailed comparison between OFDM and OQAM/FBMCProvides readers with a complete introduction to OQAM/FBMC, from the transmitter to the receiverGives readers an up-to-date view of future mobile communications and how QAM/FBMC supports them
Students’ Ways Of Thinking About Rate Of Change

Degisim orani, fonksiyonlarin anlasilmasinda onemli bir konudur. Aslinda degisim orani da bir fonksiyon gibi dusunulebilir. Cunku bir niceligin digerine gore degisim orani hakkinda muhakeme etmek fonksiyon kavraminin temelini olusturmaktadir. Bu calismanin amaci 8. sinif ogrencilerinin degisimin orani konusunda sahip olduklari dusunme yollarini belirlemektir. Calismanin verileri uygulanan ogretim deneyi suresince elde edilmistir. Ogretim deneyinde uygulanan gorevler ise ogrencilerin degisimin orani konusunda anlayislarini ortaya koyacak sekilde olusturulmustur. Calismanin sonuclarina gore ogrencilerin dusunme yollari niceliksel olmayan degisim orani ve niceliksel degisim orani seklinde kategorize edilebilir. Ogretim deneyinin sonucunda ogrencilerin dusunme yollari, niceliksel olmayan degisim oranindan niceliksel degisim oranina dogru degisim gostermistir.
An algorithm for selecting face features using deep learning techniques based on autoencoders

In recent years, deep learning as a part of the artificial intelligence theory has formed the basis for many advanced developments, such as drone, voice and image recognition technologies, and etc. The concept of deep learning is closely related to artificial neural networks. On the other hand deep learning techniques work with unmarked data. For this reason, deep learning algorithms show their effectiveness in face recognition. But there are a number of difficulties related to implementation of deep learning algorithms. Deep learning requires a large amount of unmarked data and long training. In this presentation a new algorithm for automatic selection of face features using deep learning techniques based on autoencoders in combination with customized loss functions to provide high informativeness with low withinclass and high between-class variance is proposed. The multilayer networks of feed forward type are used. The extracted features are used for face classification. The performance of the proposed system for processing, analyzing and classifying persons from face images is compared with that of state-of-art algorithms.
Fast and Robust Flight Altitude Estimation of Multirotor UAVs in Dynamic Unstructured Environments Using 3D Point Cloud Sensors

This paper presents a fast and robust approach for estimating the flight altitude of multirotor Unmanned Aerial Vehicles (UAVs) using 3D point cloud sensors in cluttered, unstructured, and dynamic indoor environments. The objective is to present a flight altitude estimation algorithm, replacing the conventional sensors such as laser altimeters, barometers, or accelerometers, which have several limitations when used individually. Our proposed algorithm includes two stages: in the first stage, a fast clustering of the measured 3D point cloud data is performed, along with the segmentation of the clustered data into horizontal planes. In the second stage, these segmented horizontal planes are mapped based on the vertical distance with respect to the point cloud sensor frame of reference, in order to provide a robust flight altitude estimation even in presence of several static as well as dynamic ground obstacles. We validate our approach using the IROS 2011 Kinect dataset available in the literature, estimating the altitude of the RGB-D camera using the provided 3D point clouds. We further validate our approach using a point cloud sensor on board a UAV, by means of several autonomous real flights, closing its altitude control loop using the flight altitude estimated by our proposed method, in presence of several different static as well as dynamic ground obstacles. In addition, the implementation of our approach has been integrated in our open-source software framework for aerial robotics called Aerostack.
Minimum Out-of-Order Core

Mobile computing has grown drastically over the past decade. There are already more than 2 billion mobile devices in circulation worldwide [1] and the number of mobile subscribers is expected to cross the 6 billion mark in coming years [2]. A high-quality user experience and longer battery life are the key challenges in building competent mobile devices including smartphone, tablets, and other handheld devices. To meet the heavy processing demands of high-quality user experience, these devices generally deploy out-of-order (OoO) processing cores. However, the high energy requirements of OoO execution directly limit the battery life. This work investigates a minimum out-of-order core that approaches the performance of full OoO execution, however, only at a fraction of its energy cost. In pursuit of performance, an OoO core exploits an application’s inherent instruction level parallelism (ILP) by executing independent instructions out of the program order. However, it employs a number of large, complex, and power hungry hardware structures such as instruction queue (IQ), physical register files (PRF), and load/store queues (LSQ) etc. to expose the ILP. Instruction queue, which is typically implemented as a content addressable memory (CAM), is arguably the most complex and power hungry structure of an OoO core. It comprises a complex web of wires and combinational circuits to broadcast the results (or physical register ids) to make waiting instructions ready for execution and select among ready instructions based on set priorities. Furthermore, to a first order, the complexity and power consumption of IQ increases quadratically with issue width and linearly with the number of entries. In this work, we study the behaviour of SPECcpu2006 workloads and discover that not all instructions need to pass through these complex OoO structures to expose ILP. In particular, as shown in Figure 1, we found that in a typcial mobile core, with 128 ROB entries and 4-wide issue, about 28% of the instructions are ready for execution when they are dispatched to the IQ, we call these Ready at Dispatch (R@D) instructions. Also, a further 15% of instructions become ready within 2 cycles after dispatch, called Almost Ready at Dispatch AR@D instructions. Based on these results, we make a critical observation that a complex IQ brings little or no ILP benefits for these instructions as they can execute in program order with minimal stalls. Our second key observation is that the values/results passed among R@D and/or AR@D instructions em sDTD bzip2 dalII gobm k rom cs hm m er libantum m cf m ilc am d om ntpp pvray seng splex rf xancbm k VG 0 10 20 30 40 50 60 70 80 90 100
Judging spatial relevance and document location for Geographic Information Retrieval

Finding documents relevant to queries which include some geographical context is key to successful Geographic Information Retrieval (Larson, 1996). Such queries typically consist of a triplet containing a theme, spatial relationship and location, for example <castles><near><Edinburgh>. SPIRIT (Jones et al., 2004) is a prototype spatially-aware search engine designed to deal with such queries by considering not only the textual content of documents, but also assigning multiple geographic footprints to all toponyms identified within document text (Clough, 2005).
Survey of Cyber Moving Targets Second Edition

This survey provides an overview of different cyber moving-target techniques, their threat models, and their technical details. A cyber moving-target technique refers to any technique that attempts to defend a system and increase the complexity of cyber attacks by making the system less homogeneous, static, or deterministic. This survey describes the technical details of each technique, identifies the proper threat model associated with the technique, as well as its implementation and operational costs. Moreover, this survey describes the weaknesses of each technique based on the current proposed attacks and bypassing exploits, and provides possible directions for future research in that area.
Comparative study of Named-Entity Recognition methods in the agronomical domain

Text mining is becoming an important part of research topic in biology with the original purpose to extract biological entities such as genes, proteins and traits to extend the knowledge from scientific papers. However, few thorough studies on text mining and applications are developed for plant molecular biology data, especially rice, thus resulting a lack of datasets available to train models. Since there is no/rare benchmark for rice, we have to face various difficulties in exploiting advanced machine learning methods for accurate analysis of rice bibliography. In this article, we developed a new training datasets (Oryzabase) as the benchmark. Then, we evaluated the performance of several current approaches to find a methodology with the best results and assigned it as the state of the art method for our own technique in the future. We applied Name Entities Recognition (NER) tagger, which is built from a Long Short Term Memory model, and combined with Conditional Random Fields (LSTM-CRF) to extract information of plant genes and proteins. We analyzed the performance of LSTM-CRF when applying to the Oryzabase dataset and improved the results up to 89% in F1. We found that on average, the result from LSTM-CRF is more exploitable with the new benchmark.
An Aspect-Sentiment Pair Extraction Approach Based on Latent Dirichlet Allocation

Online user reviews have a great influence on decision-making process of customers and product sales of companies. However, it is very difficult to obtain user sentiments among huge volume of data on the web consequently; sentiment analysis has gained great importance in terms of analyzing data automatically. On the other hand, sentiment analysis divides itself into branches and can be performed better with aspect level analysis. In this paper, we proposed to extract aspect-sentiment pairs from a Turkish reviews dataset. The proposed task is the fundamental and indeed the critical step of the aspect level sentiment analysis. While extracting aspect-sentiment pairs, an unsupervised topic model Latent Dirichlet Allocation (LDA) is used. With LDA, aspect-sentiment pairs from user reviews are extracted with 0.86 average precision based on ranked list. The aspect-sentiment pair extraction problem is first time realized with LDA on a real-world Turkish user reviews dataset. The experimental results show that LDA is effective and robust in aspect-sentiment pair extraction from user reviews.
Validation of a Wearable Sensor Insole Device for Analysis of Postural Control

VALIDATION OF A WEARABLE SENSOR INSOLE DEVICE FOR ANALYSIS OF POSTURAL CONTROL by Frank Theodore Price Postural control is a complex system in which the nervous system regulates information from various sensory systems, leading to corrective movement via the musculoskeletal system to maintain upright stance. When one or more of these systems is impaired, a person’s balance can be negatively affected. To determine the root cause of balance complications, a person may undergo clinician-supervised qualitative tests, which can be subjective in nature and may not detect small changes over time which contribute to balance issues. A new technology, the OpenGo SCIENCE (Moticon GmbH, Germany), is a pair of sensor insoles which applies wearable technology to evaluate motion. 20 subjects, aged 20-25, conducted 10 bipedal stance trials (5 eyes-open, 5 eyes-closed) wearing the OpenGo in-shoe and on a research-grade force plate simultaneously. A selection of linear, nonlinear, and frequency-domain measures of postural control were compared between the two devices to assess the validity of the OpenGo for analysis of quiet stance. It was found that COP range and RMS (AP-direction), 95% confidence ellipse area, approximate and sample entropy (ML-direction), median frequency, and low-frequency power ratio are considered valid to use for balance assessment using the sensor insole device, but special care must be taken during data post-processing. VALIDATION OF A WEARABLE SENSOR INSOLE DEVICE FOR ANALYSIS OF POSTURAL CONTROL