Miracle-dz/UniFAR-FTUs huggingface dataset:
Affinity Propagation: Clustering Data by Passing Messages

2009 Clustering data by identifying a subset of representative examples is important for detecting patterns in data and in processing sensory signals. Such " exemplars " can be found by randomly choosing an initial subset of data points as exemplars and then iteratively refining it, but this works well only if that initial choice is close to a good solution. This thesis describes a method called " affinity propagation " that simultaneously considers all data points as potential exemplars, exchanging real-valued messages between data points until a high-quality set of exemplars and corresponding clusters gradually emerges. Affinity propagation takes as input a set of pairwise similarities between data points and finds clusters on the basis of maximizing the total similarity between data points and their ex-emplars. Similarity can be simply defined as negative squared Euclidean distance for compatibility with other algorithms, or it can incorporate richer domain-specific models (e.g., translation-invariant distances for comparing images). Affinity propagation's computational and memory requirements scale linearly with the number of similarities input; for non-sparse problems where all possible similarities are computed, these requirements scale quadratically with the number of data points. Affinity propagation is demonstrated on several applications from areas such as computer vision and bioinformatics, and it typically finds better clustering solutions than other methods in less time. ii Acknowledgements I would first like to acknowledge and thank my wife, Candice, for her support and encouragement through my educational journey. I'd also like to thank my family for their backing, and more practically, my father for spending many hours carefully proofreading this thesis. I have had many valuable experiences at the University of Toronto during my graduate studies, so I would like to acknowledge some of the people who helped me along. I would like to thank my Ph.D. supervisor, Brendan Frey, for guiding me through graduate studies and helpful discussions that spawned much of my research — most notably, affinity propagation. I would also like to thank the members of my Doctoral Supervisory Committee from both theve appreciated the insights and ideas they shared with me which have no doubt led to a better finished product. I would also like to thank John Winn of Microsoft Research (Cambridge, UK) who agreed to be my external examiner in spite of facing many other commitments at the time. I would like to thank my fellow members of Brendan Frey's Probabilistic and Statistical Inference group …
Concentración de adiponectina posterior a reducción de masa corporal en un grupo de mujeres obesas premenopáusicas en Lima, Perú

Objective: To investigate the changes in the plasma-circulating adiponectin concentration in 23 premenopausal obese women living in Lima after a body mass reduction as a result of an aerobic physical activity program and a low-calorie diet. Materials and methods: An analytical and quasi-experimental study was conducted in a group of obese women. In addition, another 24 women were considered as control or reference group for comparing their adiponectin concentration and other biochemical markers. The quantification of adiponectin was carried out using the ELISA test. Fasting blood glucose concentration, cholesterol, high-density lipoprotein and triglycerides levels were quantified by routine clinical analysis. Results: Before beginning the program, the control group showed high adiponectin levels (median, 8.54 µg/mL; range, 6.14 µg/ mL to 13.49 µg/mL) compared to the obesity group (median, 7.03 µg/mL; range, 3.77 µg/mL to 17.23 µg/mL). However, the difference was not statistically significant (P = 0.0563). Once the program was finished, the obesity group showed a statistically significant reduction in the body mass index (P = 5.98e-08) and abdominal circumference (P = 1.55e-08), and a statistically significant increase in the adiponectin levels (median, 8.79 µg/mL; range, 5.50 µg/mL to 19.37 µg/mL) (P = 0.0127). Conclusions: Based on the results, we conclude that the adiponectin concentration in premenopausal obese women increases when the body mass is reduced as a result of aerobic physical activity and a low-calorie diet.
ÖRGÜTSEL NOSTALJİNİN İŞTEN AYRILMA NİYETİ ÜZERİNE ETKİSİNDE İŞİN ANLAMLILIĞININ ARACILIK ROLÜ

Orgutsel nostalji kavrami orgutsel davranis yazininda uzerinde arastirma yapilan yeni kavramlardan birisidir. Orgutsel nostalji, bir calisanin onceden veya halen calistigi orgutte gecmiste yasadigi olaylara veya gecmis is yasantisina duydugu ozlem olarak tanimlanmaktadir. Az sayida arastirma, orgutsel nostalji duygusu tasiyan calisanlarin isine yukledigi anlam ve isten ayrilma niyeti arasinda bir iliskinin oldugunu ortaya koymaktadir. Bu arastirmanin amaci ise, isin anlaminin orgutsel nostalji ve isten ayrilma niyeti arasindaki iliskideki oynadigi rolu tespit etmektir. Bu kapsamda perakende sektoru calisanlari arastirmanin orneklemini olusturmaktadir. Kolayda ornekleme yontemi kullanilarak perakende hizmet sektorunden toplamda 401 calisana ulasilmistir. Arastirmanin bulgularina gore isin anlaminin orgutsel nostalji ile isten ayrilma niyeti arasindaki iliskide tam araci rolu oldugu tespit edilmistir. Bu calisma neticesinde orgutsel nostalji ile isin anlami arasinda pozitif yonlu ve anlamli, isten ayrilma niyeti ile negatif yonlu ve anlamli iliskiler bulunmustur. Bunun yani sira, isin anlami ile isten ayrilma niyeti arasinda negatif yonlu anlamli iliski oldugu anlasilmistir.
A mix-grained architecture for improving HLS-generated controllers on FPGAs

With the recent slowdowns in traditional technology scaling, hardware accelerators, such as Field Programmable Gate Arrays (FPGAs), offer the potential for improved performance and energy efficiency compared to general purpose processing systems. While FPGAs were traditionally used for applications such as signal processing, they have recently gained popularity in new, larger scale domains, such as cloud computing. However, despite their performance and power efficiency, programming FPGAs remains a hard task due to the difficulties involved with the lowlevel design flow for FPGAs. High-Level Synthesis (HLS) tools aim to assist with this time-consuming task by supporting higher level programming models which significantly increases design productivity. This also makes the use of FPGAs for large scale design development for evolving applications more feasible. In this thesis we explore the potential of modifying the current FPGA architecture to better support the designs generated by HLS tools. We propose a specialized mix-grained architecture for Finite State Machine (FSM) implementation that can be integrated into existing FPGA architectures. The proposed mix-grained architecture exploits the characteristics of the controller units generated by HLS tools to reduce the control-path area of the design. We show that our proposed architecture reduces the area of the next state calculation in FSMs by more than 3X without impacting the performance and often reducing the critical path delay of the next state calculation in FSMs.
Developmental changes in sound localization precision under conditions of the precedence effect.

DEVELOPMENTAL CHANGES IN SOUND LOCALIZATION PRECISION UNDER CONDITIONS OF THE PRECEDENCE EFFECT SEPTEMBER, 1991 RUTH Y. LITOVSKY, B.A., WASHINGTON UNIVERSITY M . A . , WASHINGTON UNIVERSITY Ph . D . , UNIVERSITY OF MASSACHUSETTS Directed by: Professor Rachel K. Clifton In enclosed spaces, the first sound that reaches the ears emanates directly from the original source, and is followed by reflections of the same sound off nearby surfaces. The ability to suppress the echoes is thought to minimize distraction and facilitate accurate localization of the original sound source. The ability to give perceptual priority to the original sound source under these conditions has long been known, and has been termed the "law of the first wave-front", or the "precedence effect" (PE). This phenomenon has been studied with respect to whether subjects perceive the presence of the lagging sound. Past developmental research on the PE has only considered the precision with which the leading or lagging stimulus can be located to a hemifield. Moreover, little attention has been paid to the influence that echoes exert on localization accuracy for the leading sound.
A note on maximal matchings in rooted products of paths and short cycles

A matching M in a graph G is maximal if it cannot be extended to a larger matching in G. The enumerative properties of maximal matchings are much less known and researched than for maximum and perfect matchings. In this paper we present the recurrences and generating functions for the sequences enumerating maximal matchings in rooted products of paths and short cycles. We also analyze the asymptotic behavior of those sequences.
Diagnostic comparison of water tree growth in XLPE insulated power cables produced in GCC countries

Electric power utilities and industrial units in Saudi Arabia are extensively using XLPE cables produced in the Arabian Gulf region. Due to prevailing high temperatures and high sulphate content in the soil coupled with high sub surface water table, these cables have suffered serious breakdowns in a short time span after their installation. This investigation was undertaken to compare the resistance to water treeing in of kV, XLPE insulated cables of four regional manufacturers that are producing these cables according to international standards. In first stage, aging was carried out under high electric stress and temperature cycling in the presence of deionized water. After 120 days of this aging, their remaining dielectric strength was determined. These results showed poor performance of one type while the others exhibited close values. In the second stage, the cables were aged in the presence of aqueous ionic solution of CuSO4 for aging periods that lasted in the range of 500 to 1500 hours. Water tree population and tree lengths were compared and their number and length distributions were subjected to statistical Weibull and Log-normal models. Water tree population and their length distributions were found to fit better on Log-normal model. This suggests that the most likely mechanism for environmentally induced water tree degradation is electromechanical fatigue based. On the other hand, water tree density as a function of aging period was found to obey a log-linear relation. These data also show that water tree density in these cables as evaluated in the second stage of aging, comparatively varies significantly and leads to better segregation and selection of the cable that will serve the best in such environmental conditions. Proceedings of the 6 ICEENG Conference, 27-29 May, 2008 EE006 2
Scene-parsing for disaster environments by means of a convolutional neural network

Disaster robotics poses particular challenges for computer vision, both in terms of image material characteristics (due to motion blur, difficult light conditions, lack of up/down orientation, etc.), and in terms of learning data (limited availability, difficulty of annotation due to image quality, etc.). We developed a system for real-time scene-parsing, intended for use in a support system for operators of remote-controlled mobile robots employed in disaster areas. Our testbed is video footage gathered by a snake-like mobile robot exploring an (artificial) collapsed building environment. The core of the system is a relatively small-scale convolutional neural network. Our approach combines pixel-level learning with superpixel-level classification, in an effort to learn efficiently from a relatively small number of partially annotated frames. Our classification system is capable of real-time operation, and demonstrates that convolutional neural networks can be employed effectively even under the harsh conditions imposed by disaster robotics.
Autenticação usando Sinais Biométricos: Fundamentos, Aplicações e Desafios

JAI comprises the work of senior researchers from SBC community, offering a unique opportunity for students and computer professionals to update themselves in different subjects, interacting with leaders of the most diverse research areas in Brazil. In 2019, JAI, held in Belem, comprised four mini-courses in advanced areas of knowledge in Computing. These are: 1) Introduction to the Programming of Quantum Computers; 2) How to program high performance applications with productivity; 3) Block Chains: Consensus Algorithms and Implementation in the Hyperledger Fabric Platform and 4) Authentication using Biometric Signals: Fundamentals, Applications and Challenges. These were selected from among 9 excellent proposals. The criteria took into account the reviewers' comments, the seniority of the speakers, demonstrated competence in their area of ​​activity, importance and scope of the proposed theme and potential to arouse the interest of young students, academics and professionals in the area.
İlköğretim ikinci kademe öğretmenlerinin bilgi ve iletişim teknolojilerine ilişkin kabul ve kullanım niyetleri

Bu arastirma ilkogretim ikinci kademe ogretmenlerinin bilgi ve ieltisim teknolojilerine iliskin kabul ve kullanim niyetlerinin incelenmesi amaciyla yapilmistir. Arastirma 2009-2010 ogretim yili Van il merkez ilkogretim okullari ikinci kademede gorev yapan toplam 750 brans ogretmeninden elde edilen veriler uzerinden yurutulmustur. Arastirma verileri ogretmenlerin demografik ozellikleri ve Bilgi ve Iletisim teknolojilerini (BIT) kabul ve kullanim niyetleri cinsiyet, kidem yili, brans, mezuniyet yili, bilgisayara sahip olma durumu, bilgisayar egitimi alma durumu, bilgisayar bilme duzeyi ve egitim duzeyi degiskenlerine gore incelenmistir. Arastirma sonucunda, ogretmenlerin bilgisayara sahip olma ve bilgisayar egitimi almis olma yuzdelerinin yuksek olmasina karsin BIT’i derslerinde kabul ve kullanim niyetlerine iliskin ortalama puanlarinin orta duzeyde oldugu belirlenmistir. Ogretmenlerin bilgisayar bilme duzeylerine gore ise ogretmenlerin buyuk cogunlugunun bilgisayari orta duzeyde bildikleri tespit edilmistir. Ayrica arastirma sonucunda ogretmenlerin BIT'i kabul ve kullanim niyetlerinin cinsiyet ve bilgisayar egitimi almis olma durumu degiskenlerine gore farklilik gosterdigi ancak kidem yili, brans, mezuniyet yili ve egitim duzeyine gore ise bir farklilik gostermedigi belirlenmistir
An Accurate and Simple Approach to Detect Eye Centers in Low Resolution Face Images

ABSTRACT This paper introduces a new approach for accurate eye center localization based upon optimized image gradients algorithm. The proposed approach requires pre-fetched feature descriptors to detect the accurate iris centers amongst the possible eye center candidates computed by image gradients over the face image data-set. The results of the proposed algorithm for detecting eye, iris, and iris centers over the test set images of publicly available low resolution and challenging data-set show an accuracy percentage of 98.9, 95.7, and 89.2, respectively. The comparison results obtained by the proposed approach were at par with the state-of-the-art techniques involving complex calculations and training requirements. So, the superior performance and outcome of the proposed approach show the usefulness of optimizing the results of simple image gradients by pre-fetched Scale Invariant Feature Transform feature descriptors in detecting iris centers under unconstrained environments. The proposed approach may be useful for the development of real-time eye gaze tracking application with improved robustness and accuracy.
A 'Phase Reset' Scheme for an 8-11Gb/s Bang-Bang CDR in 65nm CMOS

This thesis presents the design and implementation of a CDR with ‘phase reset. ’ By continually ‘resetting’ the phase of the recovered clock to be aligned with data, cycleslipping and bit errors during the lock process are reduced. This concept was demonstrated in a full-rate 8-11Gb/s Bang-Bang CDR in 65nm CMOS.
Detection of Malicious Applications on Facebook using Machine Learning Algorithm

The usage of online social networking sites has become a integral part of our lives. It helps us to communicate with our dear and distanced ones. We can also use these sites for various media sharing purposes such as music, videos, etc. Also, these days these sites are gaining much more popularity due to the third party applications that exist on these platforms. However, intruders have realized the potential of these applications and use it as a medium to spam users. In a lot of cases, according to a survey done these applications are malicious. A spammer can benefit from these applications in various ways like, can reach a large number of users, can obtain user’s personal information, and also with the help of a single user, he can spam a lot other users too. As the research goes on, research communities have focused on detecting malicious URLs and online social campaigns which are fake or spam. Here we develop an application, SecureU app, we help detect malicious application, fake or spam messages, hide pictures and posts which are inappropriate and it will also help us to give real time notifications.
DIAGNOSA GANGGUAN SALURAN PERNAFASAN MENGGUNAKAN JARINGAN SYARAF TIRUAN BACKPROPAGATION

Penelitian ini dilakukan untuk membuat aplikasi yang dapat melakukan diagnosa gangguan saluran pernafasan. Jaringan syaraf tiruan telah benyak digunakan untuk menyelesaikan berbagai macam permasalahan, salah satu permasalahan tersebut adalah pengambilan keputusan berdasarkan pelatihan yang diberikan. Aplikasi jaringan syaraf tiruan dapat diterapkan dalam berbagai bidang, salah satunya pada bidang kesehatan. Dalam penelitian ini Aplikasi jaringan syaraf tiruan digunakan untuk prediksi penyakit saluran pernafasan khususnya pada penyakit Asma, Bronkitis, Pneumonia, dan TBC berdasarkan gejala-gejala dari penyakit tersebut. Aplikasi ini menggunakan 11 unit masukan, 11 unit tersembunyi, dan 4 unit keluaran. Metode yang digunakan adalah metode Bakcpropagation. Data yang digunakan pada penelitian ini sebanyak 135 data, 115 data digunakan untuk pelatihan, dan 20 data untuk pengujian, data ini didapat dari ruang rekam medik rumah sakit Haji Surabaya. Aplikasi ini menggunakan maksimum iterasi sebanyak 1000, learning rate 0.2, dan target error sebesar 0.00000001. Hasil pengujian pada data pelatihan terhadap 115 data didapat hasil keakuratan 98% dan nilai error 2%. Error tersebut dapat terjadi karena terdapat data pelatihan yang hampir sama. Tetapi pada pengujian data didapat keakuratan sebesar 100%.
aCAVE: augmented CAVEs for entertainment applications

CAVE systems have been around virtual reality for quite some time. These systems immerse users in a cube-like environment where images are projected into its walls. Usually, in these systems interaction occurs only in the virtual space -- there is no interaction with virtual or physical objects in the physical space that comprises the CAVE. Meanwhile, there is a growing trend about mobile and accessible HMD devices arriving at the mass market, which brings exciting opportunities for research in virtual reality and entertainment applications. Considering these two issues, in this paper we present the aCAVE system (augmented CAVE) for entertainment applications that addresses the first issue by using HMD devices. In aCAVE, a user wears a see-through HMD that enables him/her to interact with other users, physical objects, and virtual objects while seeing the physical (CAVE interior) and virtual spaces (the virtual world projected in the CAVE walls). As a proof of concept we discuss the architecture and implementation of a testbed aCAVE application, which enables the user to navigate under a simulated sea and interact with virtual fishes. Many devices have been developed to allow a better user immersion. In aCAVE, we see an example that is possible to join certain devices, commonly used in virtual reality, to provide a better immersion to the user. Although this system has the goal to place a person in a virtual environment, the connection is made in a passive way, where the person has the ability to feel inside a virtual environment, walk through it and look around it, receiving all the information but not interfering in it. In order to test the proposed improvements we implemented an aCAVE application integrated with the MYO Armband, where the user participates of a volleyball match.
On Efficiently Answering Why-Not Range-Based Skyline Queries in Road Networks (Extended Abstract)

The range-based skyline (r-skyline) query on road networks retrieves the skyline objects of taking each point within a road region as a query point, in terms of objects' spatial and non-spatial attributes. In this paper, we systematically carry out the study of why-not questions on the r-skyline query in the road network (abbreviated as the why-not RSQ problem). We present three modification strategies, including modifying the query range, modifying the why-not point, and modifying both of them, for the why-not RSQ problem. In particular, a suite of newly presented effective concepts/techniques are leveraged, such as the concepts of skyline scope and skyline dominance region, non-spatial attribute modification pruning, and G-tree index. Extensive experiments using both real and synthetic data sets demonstrate the performance of our proposed algorithms.
Game Theory for Proactive Dynamic Defense and Attack Mitigation in Cyber-Physical Systems

While there has been a great deal of security research focused on preventing attacks, there has been less work on how one should balance security and resilience investments. In this work we developed and evaluated models that captured both explicit defenses and other mitigations that reduce the impact of attacks. We examined these issues both in more broadly applicable general Stackelberg models and in more speciﬁc network and power grid settings. Finally, we compared these solutions to existing work in terms of both solution quality and computational overhead.
Incorporating expert knowledge in decision support for logistics

Decision support within transport companies should not only use traditional objective functions, but also reason about qualitative effects on all involved actors. We propose a fuzzy logic rule base that can be used in addition to traditional operation research tools to calculate not just optimal solutions, but solutions that are optimal with respect to knowledge about the preferences and long-term effects on customers, employees, and the environment. We propose a fuzzy logic based judge module that is capable of evaluating logistical performance considering all parties involved in the act transporting a container. It is based on measurements of selected key performance indicators that are fuzzified and combined into satisfaction scores of customers, employees and society. Our proposed method not only enables the continuity of the quality of planning by storing and maintaining valuable expert knowledge, but can also explain decisions based on this knowledge.