Miracle-dz/UniFAR-FTUs huggingface dataset:
Feature-Driven Interactive Recommendations and Explanations with Collaborative Filtering Approach

Recommender systems (RS) based on collaborative filtering (CF) or content-based filtering (CB) have been shown to be effective means to identify items that are potentially of interest to a user, by mostly exploiting user’s explicit or implicit feedback on items. Even though, these techniques achieve high accuracy in recommending, they have their own shortcomingsso hybrid solutions combining the two techniques, have emerged to overcome their disadvantages and benefit from their strengths. Another general problem can be seen in the lack of transparency of contemporary RS, where the user preference model and the recommendations that represent that model are neither explained to the current user nor the user can influence the recommendation process except for rating or re-rating (more) items. In this paper, we first enhanced the CF approach by modelling user preferences based on items’ features in a complex product domain. The user-feature model is then used as an input to the user-based CF to generate recommendations and explanations. With our proposed approach, we aim to increase transparency and offer richer interaction possibilities in current Recommender Systemswhere users are allowed to express their interests in terms of features and interactively manipulate their recommendations through existing user profile and explanations.
Spotivibes: Tagging Playlist Vibes with Colors

Music is often both personally and affectively meaningful to human listeners. However, little work has been done to create music recommender systems that take this into account. In this demo proposal, we present Spotivibes: a first prototype for a new color-based tagging and music recommender system. This innovative tagging system is designed to take the users' personal experience of music into account and allows them to tag their favorite songs in a non-intrusive way, which can be generalized to their entire library. The goal of Spotivibes is twofold: to help users better tag their playlists to get better playlists and to provide research data on implicit grouping mechanisms in personal music collections. The system was tested with a user study on 34 Spotify users.
Implicit Knowledge Completion Using Relevance Calculation of Distributed Word Representations

In this paper, we propose a method to automatically discover implicit knowledge for events. In recent approaches researchers calculate relevance between two events appearing in the same document from news articles using distributed representations for machine learning. Since such methods handle only explicitly written information, it is very difficult for a machine to, for example, automatically answer questions about context. We acquire temporal events and calculate their implicit relationship by relevance using distributed representation of words. Likewise, relevant places are also added by using similar algorithm to enrich text with implicit knowledge. Our proposed method utilizes raw text corpus, does not require prior knowledge, and is task-independent. Experiments were performed to show temporal and semantic naturalness of the proposed knowledge completion process.
Investigating Mechanisms for User Integration in the Activity Goal Recommendation Process by Interface Design

In the field of physical activity recommendation, we have to deal with many confounding variables that lead to high result uncertainty. Assuming that users’ competence is an essential factor for reduction of the problem of inaccurate recommendations, we present and evaluate an approach on how to integrate users in the recommendation process. We investigate if and how interface element design can contribute to understanding, reflection and modification of the recommendation result. In the work described here, we use interface elements that allow for planning of physical activity goal striving. Results show that such interface elements can principally empower users, support recommendation reflection and stimulate user interaction with the recommendation.
Government Financial Support of Higher Education and its Role in Economic Prosperity of a Society

This study focuses on the role of government higher education funding in building the economic capacity of national economy. Contemporary development and competitiveness of any country crucially depends on innovations. The ability of business to provide them is directly connected with available human capital resources. Government financial support of education ensures human capital development. Government budget funding of education is one of the biggest sources of higher education funding, and thus influences economic prosperity fostering GDP per capita growth. The article purpose is to examine government higher education expenditures impact on GDP per capita growth. The research methodology uses panel data analysis based on R statistics. The data sources are the World Bank and OECD. Literature review reveals methods of education funding and the role of government. Then, five hypotheses are posited that describe possible impact of government education funding on GDP per capita growth. To test them, four models are used. The appropriate model to reveal the government higher education funding role is the fixed-effect model. It validates the strong impact of the share of higher education expenditures in the total government expenditures on the GDP per capita growth.
Debate Outcome Prediction using Automatic Persuasiveness Evaluation and Counterargument Relations

Debates play an important educational role and proper argumentation has a power to change people’s stance on a given topic. Existing NLP research on persuasiveness of argumentation calculates it for single arguments or ranks arguments by their level of conviction. Our work extends this research by considering counterarguments. They can weaken or strengthen persuasiveness of a given argument, hence we propose novel methods to calculate persuasiveness with opinions existing in opposite stances. We create a corpus from a site containing debates where users evaluate discussions and choose winning side of a debate, allowing the calculation of opinion change. We experimentally confirmed 60.12% accuracy in the proposed debate outcome prediction task proving that additional counterargument-related information is capable to improve baseline methods.
Chaperone function: the assembly of ribulose bisphosphate carboxylase-oxygenase.

INTRODUCTION 126 TI-I~ MOLECULAR CH PERO~ CONCEPT 126 The Problem of lnteractive Surfaces 127 Assisted Self-Assembly 129 The Chaperonins 129 Tim IMPORa’ANCE OF RUBISCO 131 Properties 131 Structure 132 Synthesis 133 THE PLASTID CHAPERONIN 134 Discovery 134 Role in Rubisco Assembly by Chloroplasts 134 SYNTHESIS AND ASSEMBLY OF CLONED RtrI~ISCO IN E. coli CELLS 135 The Expression System; Synthesis and Assembly of Different Rubisco Oli#omers . 135 Overexpressed Chaperonins Promote Rubisco Assembly 136 Mutations in groES or groEL Inhibit Rubisco Assembly 139 Heat Shock Stimulates Rubisco Assembly 140
Automatic Deception Detection in RGB videos using Facial Action Units

The outcome of situations such as police interrogatory or court trials is strongly influenced by the behaviour of the interviewed subject. In particular, a deceptive behaviour may completely overturn such sensible situations. Moreover, if some specific devices such as polygraph or magnetic resonance are used, the subject is aware of being monitored and thus he may change his behaviour accordingly. To overcome this problem, in this paper a method for detecting deception in RGB videos is presented. The method automatically extracts facial Action Units (AU) from video frames containing the interviewed subject, and classifies them through an SVM as truthful or deception. Experiments on real trial court data and comparisons with the current state of the art show the effectiveness of the proposed method.
Face anti-spoofing with multi-color double-stream CNN

Previous methods on face anti-spoofing rarely pay attention to the difference of multi-channel chrominance between genuine and fake faces, or only use hand crafted features, which cannot effectively fuse multi-channel chrominance information. This paper uses CNN (convolutional neural network) features instead of hand crafted features for face anti-spoofing. In order to fuse more discriminative chrominance information, this paper proposes a novel face anti-spoofing method based on a double-stream CNN. Through the jointly modeling of features from global face image and local patches, as well as integrating the features of two different color spaces, i.e. YCbCr and HSV, we explore the discriminative representation for face anti-spoofing. Extensive experiments on benchmarks including CASIA-FASD and Replay_Attack show that our method can achieve state-of-the-art performance. Specifically, 1.79% of EER (Equal Error Rate) on the CASIA-FASD, 0.29% of EER on the Replay_Attack database are achieved.
Flow mapping and data distribution on mesh-based deep learning accelerator

Convolutional neural networks have been proposed as an approach for classifying data corresponding to labeled and unlabeled datasets. The fast-growing data empowers deep learning algorithms to achieve higher accuracy. Numerous trained models have been proposed, which involve complex algorithms and increasing network depth. The main challenges of implementing deep convolutional neural networks are high energy consumption, high on-chip and off-chip bandwidth requirements, and large memory footprint. Different types of on-chip communication networks and traffic distribution methods have been proposed to reduce memory access latency and energy consumption of data movement. This paper proposes a new traffic distribution mechanism on a mesh topology using distributer nodes by considering memory access mechanism in the AlexNet, VggNet, and GoogleNet trained models. We also propose a flow mapping method (FMM) based on dataflow stationary which reduces energy consumption by 8%.
Identifying Trojan Facebook Applications

With 20 million introduces a day, third-party applications are a noteworthy purpose behind the fame and addictiveness of Facebook. Shockingly, programmers have understood the capability of utilizing applications for spreading malware and spam. The issue is as of now huge, as we find that no less than 13% of applications in our dataset are noxious. Up until this point, the examination group has concentrated on distinguishing vindictive posts and battles. In this paper, we ask the question: Given a Facebook application, would we be able to figure out whether it is malignant? Our key commitment is in creating FRAppE — Facebook's Rigorous Application Evaluator — ostensibly the principal device concentrated on recognizing vindictive applications on Facebook. To create FRAppE, we utilize data assembled by watching the posting conduct of 111K Facebook applications seen crosswise over 2.2 million clients on Facebook. Initially, we recognize an arrangement of elements that help us recognize malignant applications from favorable ones. For instance, we find that vindictive applications frequently impart names to different applications, and they regularly ask for less authorizations than kindhearted applications. Second, utilizing these recognizing highlights, we demonstrate that FRAppE can distinguish malignant applications with 99.5% exactness, with no false positives and a high genuine positive rate (95.9%). At long last, we investigate the biological community of malevolent Facebook applications and recognize instruments that these applications use to proliferate. Strangely, we find that numerous applications conspire and bolster each other; in our dataset, we find 1584 applications empowering the viral proliferation of 3723 different applications through their posts. Long haul, we consider FRAppE to be a stage toward making an autonomous guard dog for application evaluation and positioning, in order to caution Facebook users before installing apps.
Red Blood Cell Function and Dysfunction: Redox Regulation, Nitric Oxide Metabolism, Anemia

Abstract Significance: Recent clinical evidence identified anemia to be correlated with severe complications of cardiovascular disease (CVD) such as bleeding, thromboembolic events, stroke, hypertension, arrhythmias, and inflammation, particularly in elderly patients. The underlying mechanisms of these complications are largely unidentified. Recent Advances: Previously, red blood cells (RBCs) were considered exclusively as transporters of oxygen and nutrients to the tissues. More recent experimental evidence indicates that RBCs are important interorgan communication systems with additional functions, including participation in control of systemic nitric oxide metabolism, redox regulation, blood rheology, and viscosity. In this article, we aim to revise and discuss the potential impact of these noncanonical functions of RBCs and their dysfunction in the cardiovascular system and in anemia. Critical Issues: The mechanistic links between changes of RBC functional properties and cardiovascular complications related to anemia have not been untangled so far. Future Directions: To allow a better understanding of the complications associated with anemia in CVD, basic and translational science studies should be focused on identifying the role of noncanonical functions of RBCs in the cardiovascular system and on defining intrinsic and/or systemic dysfunction of RBCs in anemia and its relationship to CVD both in animal models and clinical settings. Antioxid. Redox Signal. 26, 718–742.
Pengenalan Wajah Berdasarkan Fitur Wajah Menggunakan Opencv Python Dan Deeplearning

Dimulai dari dekade terakhir beberapa metode berbeda telah direncanakan dan dikembangkan dalam prospek pengenalan wajah yang merupakan salah satu zona perangsang utama di bidang pemrosesan gambar. Proses pengenalan wajah memiliki berbagai aplikasi dalam prospek sistem keamanan dan sistem investigasi kejahatan. Penelitian ini pada dasarnya terdiri dari tiga fase, yaitu, deteksi wajah, ekstraksi fitur wajah dan pengenalan wajah. Fase pertama adalah proses deteksi wajah di mana wilayah yang diminati yaitu, fitur wilayah diekstraksi. Fase 2 adalah ekstraksi fitur. Di sini fitur wajah, mata, hidung, dan bibir diekstraksi mulai dari area wajah yang diekstraksi. Modul terakhir adalah fase pengenalan wajah yang memanfaatkan mata kiri yang diekstraksi untuk tujuan pengenalan dengan menggabungkan fitur fitur Eigenfeatures dan Fisherfeatures .
Diagnosis and predictive clinical and para-clinical cutoffs for diabetes complications in Lur and Lak populations of Iran; a ROC curve analysis to design a regional guideline

Introduction: American Diabetes Association updates its guideline every year. However this guideline can be changed for different populations based on their cultural and genetic status. Objectives: We intend to design a regional study in Lur and Lak populations of Iran using receiver operating characteristics (ROC) curve model. Patients and Methods: A total of 133 diabetes mellitus (DM) patients were enrolled in this study. The collected information for each patient were gender, age, body mass index (BMI), DM type, DM duration, fasting blood sugar (FBS), hemoglobin A1c (HbA1c), lipid profile, type of treatments, type of statin and dose, documented neuropathy, documented nephropathy, symptomatic retinopathy, peripheral vessel disease (PVD), documented cardiovascular disease (CVD), food ulcer history, dawn effect, systolic blood pressure (SBP), and diastolic blood pressure (DBP). ROC curve was used and area under curve (AUC) was reported. Results: For neuropathy, age was the most accurate diagnostic index (area under curve [AUC] = 79%). For nephropathy SBP was the most accurate diagnostic index (AUC= 88%). For symptomatic retinopathy DM duration was the most accurate diagnostic index (AUC= 81%). For PVD, HDL-C was the most accurate diagnostic index (reverse AUC= 67%). For CVD age was the most accurate diagnostic index (AUC= 81%). For foot ulcer history age was the most accurate diagnostic index (AUC= 85%). Conclusion: The final suggested guideline is like the international guidelines. However some unique points should be regarded. Blood pressure >165/110 mm Hg is diagnostic of diabetic nephropathy. Additionally serum high-density lipoprotein (HDL-C) >48 mg/dL is strongly suggested.
Reasons to Remedies: Framing of Terrorist Attacks in Major Urdu and English Newspapers of Pakistan

Twenty first century has witnessed a new kind of war, “War on Terror”. Pakistan joined this war after the terrorist attacks of 9/11 and became a front line state in this war. Resultantly, Pakistan had to end its support for the Taliban regime in Afghanistan. The Afghan Taliban did not accept that policy shift and in reaction began attacking almost every place and segment of society right from military to politicians, mosques to parks, and hospitals to schools. The relationship between media and terrorism is indispensable because terrorists need media coverage and publicity, and media needs shocking and sensational news stories. Given this backdrop, this study intends to investigate two research questions. First, “What reasons of terrorist attacks were discussed in the editorials of major Urdu and English newspaper of Pakistan? ” and second, “What solutions were suggested in the major Urdu and English newspaper of Pakistan? ” Two newspapers, daily Dawn (English Newspaper) and daily Jang (Urdu Newspaper) have been selected for this study. Content analysis has been used as methodology and editorials published during 2001 to 2016 constitute the population for this research study. The results show that shift in foreign policy of Pakistan towards Afghanistan was discussed as a major reason of terrorist attacks and similarly, as solution, review of foreign policy of Pakistan towards Afghanistan was discussed in highest number of editorials.
Lung cancer in young patients: tumour characteristics and treatment in an Irish population

Background Lung cancer is the leading cause of cancer death in both sexes in Ireland. Studies suggest that lung cancer in younger patients has distinct characteristics. The aim of this study is to define the characteristics of lung cancer in patients 55-year-old or younger in an Irish population. Methods Data was collected retrospectively from local medical records and the hospital electronic database regarding all patients diagnosed with lung cancer aged 55-year-old and younger, from 2010–2016. Information regarding patient demographics, smoking status, tumour histology, molecular analysis, stage and location, diagnostic modality and initial treatment choice was collected. In all cases the diagnosis of lung cancer was confirmed at the regional lung cancer multidisciplinary team (MDT) meeting. Results In total, 8% (n=130) of all cases of lung cancer diagnosed from 2010 to 2016 in our center occurred in patients aged 55 years old or younger; 83% (n=108) were 45 to 55-year-old, 15% (n=19) were 35 to 44-year-old and 2% (n=3) were younger than 35-year-old; 88% (n=115) of patients reported a smoking history. There was a female preponderance (58%, n=76), higher rates of NSCLC non-squamous subtype (53%, n=69) and an upper lobe predominance (42%, n=54); 53% (n=68) of patients had IV or extensive disease at presentation. Epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase (ALK) and Kirsten rat sarcoma oncogene (KRAS) mutation rates were 9% (n=4) and 3% (n=1) and 80% (n=4) respectively. Conclusions Lung cancer in younger patients has distinct characteristics. This study suggests a female preponderance, high smoking rates and a predilection for the upper lobes. Further large-scale multicenter studies are required to verify these results and to clarify the responsible mechanisms.
INOVASI & PENGEMBANGAN E-COMMERCE - CRM DALAM MENGHADAPI GLOBASASI: STUDI KASUS - TOKOPEDIA.COM

Perkembangan e-commerce melaju dengan sangat pesat dan mengalami banyak perubahan inovasi yang signifikan. Perkembangan ini mengubah keseluruhan pola hidup manusia, mulai dari pola pikir, karakter, sikap dan pola konsumtif sehari-hari yang dimilikinya. Tokopedia merupakan salah satu perusahaan e-commerce terbesar di Indonesia yang terus mengembangkan business online menjadi sebuah entitas pelayanan yang luar biasa kepada konsumennya. Lebih jauh lagi, tokopedia memiliki banyak penawaran yang menarik serta harga yang kompetitif sehingga memenuhi kebutuhan konsumen dengan sangat baik. Dalam jurnal ini, dengan menggunakan metode The 7S McKinsey dan menganalisis dengan menghubungkan antara IT-IS-Business strategy, maka akan diperoleh inovasi apa yang seharusnya dilakukan oleh tokopedia agar dapat lebih mengembangkan sayap bisnis e-commerce yang telah dimilikinya, pelayanan CRM seperti apa yang seharusnya dilakukan oleh tokopedia sehingga loyalitas pelanggan menjadi semakin erat dari sebelumnya, bagaimana keuntungan akan mengalir kepada perusahaan dan sumber daya manusia seperti apa yang seharusnya dimiliki oleh tokopedia. Itu semua adalah merupakan sebuah tantangan besar di era globalisasi saat ini, karena persaingan antara perusahaan e-commerce saat ini sangat ketat
Photogrammetry mapping and alignment of the LMT 50-meter primary reflector

The Large Millimeter Telescope (LMT), located in central Mexico, saw completion of the final construction phase in 2017 with the installation of the full 50-meter primary reflector, following three years of operation as a 32-meter facility. The task was accomplished by adding two more concentric rings of surface segments to the existing three inner rings. Various techniques have been used previously to measure and align the 32-meter surface, including multiple laser trackers and far-field phased holography. Whilst the former method is time-consuming, requiring a full night to obtain a single surface map, holography provides low spatial resolution and requires removal of the secondary reflector for installation of the twin-horn receiver at the primary focus. Photogrammetry has been used as an alternative measurement technique for the 32-m primary since 20151, and has gradually replaced our use of holography and laser trackers for this task2 during recent years. Once the object has been targeted, photogrammetry maps may be obtained in around one hour. The technique does not require the installation of special equipment on the antenna, and has the advantage of allowing surface maps to be taken at any chosen elevation. The main drawbacks for the LMT application are environmental, since the antenna operates without an enclosure; strong winds may prevent use of the site tower crane for image taking, while the formation of condensation and frost on the reflector surface will "switch off" the reflective targets. In this paper we discuss comparative measurements taken as the first outer segments were installed, and the use of photogrammetry to carry out the alignment of the fully installed 50-meter surface. At the time of writing this activity is still in progress, however full-surface alignment to the order of just over 100 microns was achieved quite quickly, with multiple elevation maps allowing the development of a usable 50-m active surface model for compensation of gravitational distortions.