Miracle-dz/UniFAR-FTUs huggingface dataset:
Biyografik Anlatıya Dayalı İnanç Gelişimi Biçimleri ve Nicel Ölçümler

Bu calismada Fowler (1981) tarafinda gelistirilen inanc gelisimi kuraminin, Turkiye baglaminda 91 kisiyle nitel olarak yapilan arastirmalar cercevesinde kuramsal olarak yeniden gozden gecirilmis bir modeli yer almaktadir. Kurama yapilan elestirel yaklasim sonucu kulturel-yerel baglam dikkate alinarak bir inanc asamalari, inanc semalari ve semalarin gelisim cizgileri modeli belirlenmistir. Ayrica, inancin oteden beri bilinen yapi (kesin-esnek) ve icerik (konvansiyonel-dini–konvansiyonel olmayan-sekuler) boyutlari iki uclu bicimde somutlastirilarak inanc semalari, gelistirilen modelde bu iki boyut uzerine yerlestirilmistir. Model su sekilde sunulmustur: Once daha genel bir yapiya sahip olan inanc asamalari Fowler’in modeli cercevesinde ve ek asamalar onerilerek Mitsel-Literal inanc, Yapay-Konvansiyonel Inanc, Yogun Inanc, Gerilimli Inanc, Bireysel-Dusunsel Inanc ve Birlestirici inanc olarak belirlenmistir. Ardindan bu asamalardan her biri icerisinde dusunulen ornegin Bireysel-Dusunsel Inanc asamasi icinde yer alan Bireysel-Dini Inanc semasi vb. gibi birden cok inanc semalarindan soz edilmistir. Fowler’in tek gelisim cizgisi vurgusundan farkli olarak bu calismada inancta gelisimin inanc asamalari duzeyinde tek olmasina karsilik semalar duzeyinde birden cok sekilde olabilecegi uzerinde durulmustur. Bu gelisim cizgileri ornekleri de Yogunlasma Yonelimli, Bireysel Inanc (Bireysel-Dini ve Bireysel-Sekuler Inanc) yonelimli, Reaksiyonel ve/ya Donusum Yonelimli, Arayis Yonelimli ve Birlestirici Inanc Yonelimli olarak isimlendirilmistir. Calismanin ikinci asamasinda gelistirilen bu yeni modelin (inanc asamalari, semalar ve gelisim cizgileri) nicel olarak olculebilmesi icin Turkiye’nin iki ayri sehrinde yer alan iki universitedeki 934 ogrenciyle yapilan bir arastirma sonucunda coklu bir olcek bataryasi hazirlanmistir. Gelistirilen olcekler arasinda, literal inanc, partikularizm, kapatma ihtiyaci, gerilimli inanc (simdiki zamanda ve gecmis zamanda), donusum, pluralizm/cogulculuk, hosgoru, gorecelilik, tarihselcilik, bireysel maneviyat olarak isimlendirilen alt olcekler yer almaktadir. Sonucta sunulan bu nicel olceklerin, yurutulmesi guc ve pahali olan geleneksel inanc gelisimi gorusmesi ve analizini iceren nitel calismaya alternatif olarak bireysel inanc veya dunya gorusu semalarini ve gelisim cizgilerini gelistirilen model cercevesinde olcebilecegi ileri surulmektedir.
Gastric adenocarcinoma: 1-year overall survival, disability-adjusted life years, years of life lost, and prognostic factors—a single-institution experience

Objective To analyze factors affecting 1-year overall survival and burden of gastric adenocarcinoma in a single-institution cohort. Methods A prospective cohort study of gastric adenocarcinoma patients from a cancer center in São Paulo, Brazil, was conducted between February 2016 and July 2019. Overall survival was analyzed at 12 months post-diagnosis using the Kaplan–Meier method. A log-rank test was applied to compare curves. Sociodemographic and clinicopathological features were assessed to detect prognostic factors using univariate and multivariable Cox regression analyses to calculate hazard ratio (HR) and its confidence intervals (CIs). Disability-adjusted life years (DALY) constituted the sum of years of life lost (YLL) plus years lived with disability (YLD). YLL represented the sum of years lost before the age of 76.6 years. YLD was calculated as the number of cases multiplied by the duration and burden of the disease. YLL per death was calculated as the mean YLL for each individual. Results Overall survival at 1-year follow-up was 80.8%. The multivariable model adjusted for age and sex identified cerebrovascular disease (HR 8.5, 95% CI 3.3–21.8), stage III/IV (HR 5.7, 95% CI 2.3–13.7), diabetes (HR 3.2, 95% CI 1.5–6.6), and<9 years of education (HR 2.9, 95% CI 1.5–5.8) as prognostic factors. Out of the 214 treated cases, there was 700.72 DALY during the first year, of which 90.55% corresponded to YLL and 9.45% to YLD. The average YLL per death was 15.48 and was higher among women (19.24 YLL per death). Conclusion At a single cancer center, 1-year overall survival probability was approximately 80% in patients with gastric adenocarcinoma. Patients with a higher risk of death had cerebrovascular disease, advanced clinical staging, diabetes, and/or lower educational level. Approximately 700 years of DALY was documented, with women having the highest YLL per death. Because this study was conducted at a single cancer center, the results might not be representative of a general population. To the best of our knowledge, this study was the first to assess gastric adenocarcinoma DALY, YLL, and YLL per death in the first year of follow-up in a hospital cohort in Brazil.
Using higher-order statistics from EEG signals for developing brain-computer interface (BCI) systems

In order to characterise the non-Gaussian information contained within the EEG signals, a new feature extraction method based on bispectrum is proposed and applied to the classification of right and left motor imagery for developing EEG-based brain-computer interface (BCI) systems. The experimental results on the Graz BCI data set have shown that based on the proposed features a LDA classifier outperforms the winner of the BCI 2003 competition on the same data set in terms of the competition criterion.
Behavioral synthesis: digital system design using the synopsys behavioral compiler

1. Introduction. Design Flow. Simulation and Verification. RTL and Behavioral Design. Behavioral Compiler Design Flow. 2. Behavioral Compiler. Inputs. Behavioral Compilation: Internals. 3. HDL Descriptions. The Design. Behavioral Processes. Clock and Reset. I/O Operations. Flow of Control. Memory Inference. synthetic Components. Preserved Functions. Pipelined Components. Random Logic. 4. I/O Modes. Cycle-Fixed Mode. Superstate-Fixed Mode. Free-Floating Mode. Control Unit Registers. 5. Explicit Directives and Constraints. Labeling. Scheduling Constraints. Options. Test Benches Simulation. 6. Reports. Timing Report. Reservation Tables. State Machine Reports. Error Messages. 7. FIR Filter. Initial Design. Synthesis. Simulation. Decreasing Cost. 8. IIR Filter: Handshaking I/O Protocal. Initial Design. Simulation. Synthesis. Speeding Up the Clock. 9. The Inverse Discrete Cosine Transform: C to HDL. Initial C Code. Translation into HDL. Simulation. 10. The Data Encryption Standard: Random Logic. General Description. HDL Description. Synthesis. Use of Design Ware. 11. Packet Router. A. Construction Design Ware. B. Sythesizable Subsets.
Analisis Kesuksesan Implementasi Sistem Informasi Skripsi Pada Program Studi Teknik Informatika Universitas Pembangunan Nasional “Veteran” YOGYAKARTA

—Sejak tahun 2007, program studi TeknikInformatika UPN “Veteran” Yogyakarta telahmengimplementasikan Sistem Informasi Skrispi untukmendukung kinerja organisasi yang berkaitan denganakomodasi kebutuhan layanan skripsi. Namun padakenyataannya Sistem Informasi Skripsi belum dimanfaatkansecara maksimal. Evaluasi terhadap Sistem Informasi Skripsiperlu dilakukan untuk mengetahui faktor-faktor apa saja yangmempengaruhi kepuasan pengguna Sistem Informasi Skripsi.Penelitian ini menggunakan modifikasi model penelitiankesuksesan sistem informasi Delon dan Mclean. Modifikasiyang dilakukan adalah dengan menghilangkan variabel usedari model penelitian. Variabel use dihilangkan karena SistemInformasi Skripsi bersifat mandatory. Terdapat lima variabeldalam penelitian ini yaitu, kualitas informasi, kualitas sistem,kualitas layanan, kepuasan pengguna dan net benefit.Penelitian dilakukan dengan menganalisis hasil kuesioner yangterkumpul dari 45 responden yaitu mahasiswa yang pernahmenggunakan Sistem Informasi Skripsi. Metode analisis yangdigunakan adalah Partial Least Square menggunakan softwareSmartPLS.Hasil analisis menunjukkan kepuasan pengguna SistemInformasi Skripsi dipengaruhi oleh kualitas informasi dankualitas sistem. Net benefit dipengaruhi oleh kepuasanpengguna. Dalam penelitian ini kualitas layanan tidakmempunyai pengaruh terhadap kepuasan pengguna. Secaraumum Sistem Informasi Skripsi telah memberikan manfaatkepada pengguna, namun dalam implementasi SistemInformasi Skripsi mahasiswa sebagai pengguna merasa perluadanya peningkatan kualitas layanan dari Sistem InformasiSkripsi.Keyword—kepuasan pengguna; sistem informasi skripsi;Model Delon dan Mclean; PLS
Control of a horizontal axis wind turbine using H infinity control

An H infinity controller based on a linear model that reduces fatigue damage of a wind turbine is designed. It is important that the system be robust, especially at 1 omega /sub r/ and 3 omega /sub r/, which are the most prominent rotational disturbances which act on the system. In order to avoid actuator saturation, a detuned controller is designed. When the windspeed rises above the rated speed, the controller must unwind and attain the correct state before normal control can continue. This is achieved by splitting the detuned controller into two parts. Simulation results are presented, showing that the detuned controller overcomes the problems of actuator saturation and instability, but that the overshoots in the power and torque plots are still too large. <<ETX>>
Fuel volume measurement in aircraft using neural networks

Measurement of fuel quantity in aircraft tanks is a multidimensional estimation problem. It involves a nonlinear transformation of a set of noisy sensor signals into a single fuel quantity estimate. In a typical passenger aircraft, this calculation is usually performed by means of a set of one-dimensional, linearly interpolated look-up tables. This paper presents a neural net approach to the problem. A feedforward neural net is trained to estimate fuel quantity directly from sensor readings. A simulation example is given to compare efficiency of the neural net technique to the standard look-up table method. Practical ramifications of the proposed method are discussed.
IMPLEMENTASI METODE POHON KEPUTUSAN UNTUK KLASIFIKASI DATA DENGAN NILAI FITUR YANG TIDAK PASTI

Decision tree merupakan salah satu metode untuk mengklasifikasikan data. Model decision tree merupakan sebuah tree yang terdiri dari root node, internal node dan terminal node. Sementara root node dan internal node merupakan variabel/fitur, terminal node adalah label kelas. Dalam melakukan klasifikasi, sebuah data query akan menelusuri root node dan internal node sampai mencapai terminal node. Pelabelan kelas data query berdasarkan label di internal node. Pada Decision Tree tradisional, data yang digunakan adalah data dengan nilai fitur yang sudah pasti. Pada penelitian ini bertujuan untuk membangun suatu Decision Tree yang dapat menangani data dengan nilai fitur yang tidak pasti yaitu data yang memiliki range nilai. Selama ini penanganan data dengan fitur yang tidak pasti menggunakan metode averaging. Akan tetapi ada penelitian lain yang menyebutkan bahwa ada metode lain yang lebih handal dalam menangani data dengan nilai fitur yang tidak pasti. Metode tersebut adalah metode berbasis distribusi. Tugas akhir ini bertujuan untuk mengimplementasikan metode decision tree yang mampu menghandle fitur dengan nilai yang tidak pasti dengan menggunakan metode yang berbasis distribusi. Akurasi dari metode ini dibandingkan dengan akurasi metode averaging. Berdasarkan hasil uji coba, terbukti bahwa metode berbasis distribusi memiliki akurasi yang lebih tinggi jika dibandingkan dengan akurasi metode yang berbasis averaging. Uji coba dilakukan dengan menggunakan data iris dan data breast dari UCI.
Editing and imputation by means of neural networks

Editing and imputation of statistical data are possible because we take advantage of some prior knowledge about the type of statistical objects we investigate. The processes of editing and imputa­ tion are considered expensive parts of survey and census costs. This presentation discusses the use of neural network methodology to improve the efficiency of these processes. Two applications are discussed as demonstrations of the approach.
COMBINATION OF STATISTICAL AND LANGUAGE PROCESSING METHODS IN NEWS SUMMARIZATION: A CASE STUDY FOR VIETNAMESE NEWS

Automatic summarization refers to a technique of reducing of a text document by a computer program to create a summary that retains the most important points of the original document. Among various kinds of textual documents, news plays an important role in our life, which is always updated sequentially every day in large scale. A technique for automatic creation of new summarization would help readers to quickly capture significant information from vast amount of electronic newspapers available on the Internet nowadays. In this paper, we introduce an approach to handle this issue on Vietnamese news. By combining both statistical and linguistic methods, we are able to produce meaningful summarization of real articles collected from major newspaper channels in Vietnam.
An Introduction to Modern Econometrics Using Stata

An Introduction to Modern Econometrics Using Stata, by Christopher F. Baum, successfully bridges the gap between learning econometrics and learning how to use Stata. The book presents a contemporary approach to econometrics, emphasizing the role of method-of-moments estimators, hypothesis testing, and specification analysis while providing practical examples showing how the theory is applied to real datasets using Stata.
Power optimization of /spl Delta//spl Sigma/ analog-to-digital converters based on slewing and partial settling considerations

A technique to obtain low power /spl Delta//spl Sigma/ ADC designs under slewing and partial settling behavior of the integrators is described. /spl Delta//spl Sigma/ ADCs do not require complete settling of the integrators to the overall converter accuracy due to their oversampling and noise-shaping characteristics. When the slewing and incomplete settling behavior of the modulator are explored properly, it is possible to obtain power optimal designs. Accurate estimates are obtained under non-ideal conditions such as finite switch resistances in the sampling and the feedback paths. It is also shown that the noise reduction strategies such as correlated double sampling (CDS) significantly affect the power requirements.
Leveraging Learning and Language Via Communication Bootstrapping

© 2 0 0 3 m a s s a c h u s e t t s i n s t i t u t e o f t e c h n o l o g y, c a m b r i d g e , m a 0 2 1 3 9 u s a — w w w. a i. m i t. e d u m a s s a c h u s e t t s i n s t i t u t e o f t e c h n o l o g y — a r t i f i c i a l i n t e l l i g e n c e l a b o r a t o r y @ MIT
Digital Signal Processing Issues in the Context of Binaural and Transaural Stereophony

Signal processing aspects of the modeling of head-related transfer functions (HRTFs) are examinated, with application to the real-time mixing and synthesis of two-channel signals for headphone or loudspeaker reproduction of three-dimensional sound images. The merits of IIR and FIR implementations of the synthesis filters are discussed and efficient solutions are proposed, including time-varying implementations (allowing head-tracking or the simulation of moving sound sources). Further modeling of early reflections and the use of feedback delay networks for reproducing the later diffuse reverberation make it possible to include accurate binaural room effect synthesis in the simulation, without exceeding the capacity of recent programmable digital signal processors.
Design of Campus one-Finger Service System Based on Fingerprint Identification

In order to solve the problems of RF card that easy to lose, not recycling, waste of resources and so on, we using human fingerprint feature instead of RF card, designed a campus one-finger service system based on fingerprint identification. Integrating RF fingerprint identification technology to the digital campus system, to achieve the goal of multiple uses of fingerprint identification. We made some improvement of the existed RF fingerprint recognition module and designed a fingerprint recognition consumer terminal device based on STC processor, through a fingerprint reader to collect the teachers' and students' fingerprints and stored in the database. The STC processor real-time scanning, when a fingerprint is scanned, it will be compared with the database, if the match is successful, and the “Check button” outside is pressed, it will perform recharge or deducted operation and display the account balance. The terminal device using dual power supplies to ensure the reliability of the system. It is connected to the host computer through RS-232 interface and thus connects to the campus one-finger service system. This system has important significance for the construction of lowcarbon society. Keywords—fingerprint identification; digital campus; terminal; single chip microcomputer; check button
Reinforcement adaptive learning neural network based friction compensation for high speed and precision

There is an increasing number of applications in high precision motion control systems in manufacturing, i.e., ultra-precision machining, assembly of small components and micro devices. It is very difficult to assure such accuracy due to many factors affecting the precision of motion, such as friction and backlash in the drive system. The standard PID (proportional-integral-derivative) type servo control algorithms are not capable of delivering the desired precision under the influence of friction and backlash. In the paper, the friction and the disturbance are identified by a neural network. The weight adaptation rule, defined as a reinforcement adaptive-learning rule, is derived from the Lyapunov stability theory. Therefore the proposed scheme can be applicable to a wide class of mechanical systems. The simulation results on 1-DOF mechanical system verify the effectiveness of the proposed algorithm.
Contributions to Improve Online Learning Through Adaptive Hypermedia Techniques

Abstract The personalization of learning through the automatic adaptation of the educational process, especially for the contents, is regarded as an important and necessary step for the improvement of education in the future. It is believed that through individualization get improved efficiency, increased speed and quality of learning for students and by automating the process, improved efficiency, better resource utilization, scalability of the process learning. To achieve this goal we have developed different strategies. One of them are looking for Adaptive Hypermedia Systems adjust all contents in a atuomática to the characteristics of each user.
A Study on the Implementation of Inheritance Anomaly in Concurrent Programming

When concurrency is integrated to programming language, problem more than inheritance remains yet. Because more than inheritance happens by collision or cross fire between synchronization and inheritance of same time object, when synchronization code is not detached properly from method code about same time object, it makes expanded of code to make derivation class change synchronization code of super class and method code. In this paper, minimize right of inheritance method, When subclass is introduced to new synchronization limitation condition, wish to solve problem more than inheritance of three types that happen in same time programming embodying C++ class that do so that can avoid alteration of method reed.
Recognition of Spoken Gujarati Numeral and Its Conversion into Electronic Form

Speech synthesis and speech recognition are the area of interest for computer scientists. More and more researchers are working to make computer understand naturally spoken language. For International language like English this technology has grown to a matured level. Here in this paper we present a model which recognize Gujarati numeral spoken by speaker and convert it into machine editable text of numeral. The proposed model makes use of MelFrequency Cepstral Coefficients (MFCC) as a feature set and KNearest Neighbor (K-NN) as classifier. The proposed model achieved average success rate of Gujarati spoken numeral is about 78.13%. Keywords—speech recognition;MFCC; spoken Gujarati numeral; KNN
Modeling the speech intelligibility in fluctuating noise

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Some Considerations In Investigating Synchronous Online Delivery Of English Courses: Interfacing Qualitative And Quantitative Paradigms

E-learning is not just another add-on to the existing system of learning. It is a technologythat is transforming our educational institutions and how we conceptualise and experienceteaching and learning. Teaching online is becoming more flexible and innovative in itspreparation and delivery, as content and activities can be placed on websites for studentsboth as supplement to lectures or as replacement for them. This paper discusses how adoctoral dissertation was designed to gather information on three areas related to thesynchronous online delivery of English courses namely teaching and learning,technology, and management in a virtual institution of higher learning. It explains thedesign of the study and its rationale within the qualitative and quantitative paradigms.The discussion in this paper also attempts to highlight plausible issues that researchersmay encounter when conducting research in a technology enhanced context and suggestspractical way to consider.
Overview of Current Text-to-Speech Techniques: Part II - Prosody and Speech Generation

Speech synthesis is an increasingly important technique in interactive voice systems, and is crucial to the next generation of spoken language dialogue systems. Described here are many of the techniques and algorithms used in modern commercial text-to-speech synthesisers, where real world issues of robustness, reliability and processing cost compete with the specific requirements of naturalness and intelligibility. This paper concentrates on using the results of the linguistic analysis of the input text to generate an appropriate synthetic prosody and speech signal. The importance of the rhythmic characteristics of synthetic speech is emphasised by placing the prosody generation task within the framework of metrical phonology.
Algoritma Cluster Dinamik Untuk Optimasi Cluster Pada Algoritma K-Means Dalam Pemetaan Nasabah Potensial

Pelanggan merupakan salah satu sumber keuntungan perusahaan. Pemahaman yang baik tentang pelanggan sangat penting dilakukan untuk mengetahui nilai potensial pelanggan. Saat ini pelaksanaan CRM(Customer Relationship Management) dapat membantu dalam pemahaman nilai pelanggan. Segmentasi pelanggan adalah salah satu metode yang digunakan untuk pemetaan pelanggan. Nilai potensial pelanggan dapat diukur menggunakan metode RFM (Recency,Frequency,Monetary). Algoritma K-means salah satu metode yang banyak digunakan untuk segmentasi pelanggan. K-means banyak dipakai karena algoritma nya mudah dan sederhana, tetapi algoritma ini memiliki kekurangan yaitu sensitifitas pada partisi awal jumlah cluster(k). Untuk menyelesaikan masalah sensitifitas partisi awal jumlah cluster pada algoritma K-means, maka diusulkan algoritma cluster dinamik untuk menetapkan jumlah cluster(k). Hasil percobaan menunjukan bahwa algoritma cluster dinamik pada K-means, dapat menghasilkan kualitas cluster yang lebih optimal.