VOLTAGE-CONTROLLED SMALL SIGNAL ANALYSIS OF REAL SPACE TRANSFER TRANSISTOR

The research of determining the small signal equivalent circuit of the real space transfer (RST) transistor is investigated in this work. We propose a voltage-controlled mode model, called parameter extraction, to describe the performance of RST transistors at high frequency range. Besides, we also employ the value-determined model to simulate the microwave characteristics of RST and the theoretical and experimental results are compared. The influence of variables of RF performance is analyzed and theoretical results show that the cut-off frequency ( f T ) is mainly affected by the leakage resistances and the dimension of metal contact, but the maximum available gain frequency, f max , is dependent on contact resistances

NANOCRYSTALLINE TiO2 ELECTRODES EXHIBITING HIGH STORAGE CAPACITY AND STABILITY IN RECHARGEABLE LITHIUM BATTERIES

Nanocrystalline TiO 2 films were explored for the first time as electrode material for a rechargeable lithium intercalation cell, i.e., Li/LiCF3SO3 + PC/TiO 2. Two kinds of nanocrystalline films, TiO 2 F387 (Degussa) and TiO 2 colloid-240, were investigated. These films exhibited excellent performance renderin[s them a promising choice for secondary battery applications. At a current density of 0.01 mA/cm", two voltage plateaus at 1.78 and 1.89 V were observed for TiO 2 F387 films during charge and discharge, respectively. The TiO 2 electrode charge capacity per unit weight rose with decreasing current density. The highest capacity, obtained at a current density of 0.005 mA/cm 2 and a final discharge voltage of 1.4 V, was 265 mAh/g corresponding to a lithium insertion ratio of x--0.8. Nanocrystalline TiO_ colloid-240 films showed a similar performance. The cycle life of a TiO 2 colloid-240 cell at a high current density was found to be excellent; a capacity loss lower than 14% has been observed over 100 charge/discharge cycles

NEW RESULTS ON BANDWIDTH OF GaAs PIN PHOTODIODES

In this paper an equivalent circuit of a GaAs PIN photodiode for the millimeter wave range is proposed. Moreover, an approximate expression for the bandwidth of this circuit is obtained. By using the effective quality factor concept, an equation that includes the value of a hypothetical resistance involved in the circuit mentioned above, is derived. In the context of fiber optic communications, this "resistance" represents the losses due to the fiber-photodiode coupling

VOLTAGE-MODE UNIVERSAL BIQUADRATIC FILTER USING TWO OTAs

A four-inputs and two-outputs voltage-mode universal biquadratic filter using only two operational transconductance amplifiers (OTAs) and two capacitors is presented. The new circuits offer several advantages, such as employing the minimum number of active and passive components (two OTAs and two capacitors); the versatility to synthesize highpass, bandpass, lowpass, notch and allpass responses; high input impedance and employing only grounded capacitors for bandpass and lowpass filter realizations; some derived filter types enjoy the availability of one more simultaneously output filter response and good sensitivities performance

INSUFFICIENCIES OF THE SINGLE EXPONENTIAL MODEL AND EFFICIENCY OF THE DOUBLE EXPONENTIAL MODEL IN TIlE OPTIMIZATION OF SOLAR CELLS EFFICIENCY

Single and double exponential models are confronted to determine the most adapted model for optimization of solar cells efficiency. It is shown that the single exponential model (SEM) presents some insufficiencies for efficiency optimization. The interest of the double exponential model to optimize the efficiency and to achieve an adequate simulation of the operation of solar cells is demonstrated by means of I-V characteristics plotting

FLAT TYPE THICK FILM INDUCTIVE SENSORS

Two thick film flat-type inductive sensors are described and tested for distance and profile measurement. The first one is a single-layer spiral while the second one is a multi-layer structure consisting of ten spirals one over the other. The paper describes their geometric configurations together with their simulated magnetic fields and it reports the results from the characterization test i.e. the series-equivalent circuit parameters, the sensitivity and the cross-sensitivity to temperature. An experimental analysis of the sensitivity suggests that optimized values are obtained by an appropriate choice of the working frequency. The sensors are shielded against e.m. noise coming from the nonsensitive area. Moreover, two sensors have been tested in the laboratory using the single layer as a distance sensor and the multi-layer as a transducer for the measurement of a metallic object profile. The results of the tests show a maximum sensitivity of 14 mV=mm and a resolution of 0.6 mm for the single layer, while the multi layer one reconstructs the profile with an axial resolution of a few microns and a lateral resolution better than 200 mm

SOME CONSIDERATIONS ON TUNNELING LOSSES IN FIELD-EFFECT DEVICES FOR LOW-VOLTAGE MICROCONTROLLERS

The loss power density associated with the tunneling current in a typical MOS cell with a floating gate is evaluated for high electric-field strengths in the oxide layer. Furthermore, problems related to oxide thickness are discussed

SURFACE RECOMBINATION VIA INTERFACE DEFECTS IN FIELD EFFECT TRANSISTORS

Recombination current at the oxide-semiconductor interface of metal-oxide-semiconductor devices has been analyzed and compared with the experimental result. The activity of interface traps is dependent on the energy level and on the operating conditions. A model is shown to be powerful to describe the effect of energy level of bulk recombination centers on the values of reverse recombination current

AN ANALYTICAL STUDY ON THE LOCAL ELECTRONIC DENSITY OF STATES OF THE VALENCE BANDS IN AMORPHOUS SILICON CARBIDE

A formulation for the energy-averaged local valence band density of states of amorphous silicon carbide is derived. To this end, sp3-type hybrid orbitals are employed

SUBSPACE CLUSTERING PADA DATA MULTIDIMENSI MENGGUNAKAN ALGORITMA MAFIA

ABSTRAKSI: Data mining adalah suatu proses analisis untuk mendapatkan informasi yang penting dan terpendam dari sekumpulan data yang belum diketahui sebelumnya. Clustering merupakan salah satu fungsionalitas data mining yang digunakan untuk melakukan pengelompokan data ke dalam suatu kelas atau cluster. Prinsip dasar clustering adalah mengelompokkan objek pada suatu kelas yang memiliki kemiripan sangat besar dengan objek lain pada kelas yang sama (similarity), tetapi sangat tidak mirip dengan objek pada kelas lain (dissimilarity). Kebanyakan algoritma clustering hanya bisa menangani data yang memiliki dimensi rendah sehingga hasil clustering yang didapat kurang berkualitas. Subspace clustering adalah metode yang dapat digunakan untuk menentukan cluster yang terbentuk pada subspace yang berbeda sehingga lebih baik dalam menangani data multidimensi dibandingkan dengan cara clustering pada umumnya. Algoritma yang menerapkan subspace clustering antara lain: COSA, FINDIT, ENCLUS, CLIQUE, MAFIA, dan lain-lain.Pada Tugas Akhir ini diimplementasikan algoritma MAFIA (Merging of Adaptive Finite Intervals). MAFIA adalah algoritma clustering yang menerapkan metode subspace clustering dengan mengintegrasikan metode density-based dan adaptive-grid based sehingga algoritma ini cukup baik untuk menangani data multidimensional. MAFIA termasuk density-based methods karena melakukan clustering berdasarkan densitas dalam suatu data yang ada dan menggunakan histogram untuk menganalisis jarak antar data dalam setiap dimensi. Algoritma ini menggunakan pendekatan bottom up search untuk menemukan dense unit berdasarkan dimensi untuk mengurangi ruang pencarian. MAFIA tidak membutuhkan inputan berupa jumlah cluster yang akan dicari dalam proses clustering. Sehingga algoritma ini lebih fleksibel dalam pencarian cluster dari dataset.Algoritma MAFIA diuji menggunakan data buatan yang di-generate secara online di www.datasetgenerator.com. Hasil uji menunjukkan bahwa algoritma MAFIA baik digunakan untuk clustering data multidimensi. Kualitas ini tercermin dari maksimum akurasi yang ditemukan yaitu sebesar 0.89.Kata Kunci : clustering, MAFIA algorithm, data mining, subspace clustering.ABSTRACT: Data mining is a analize process to get important information wich is contained ing some unknow collected data. Clustering is a kind of data mining’s fungsionality wich is used to do collectivity data into class or cluster. The principle of clustering is gruoping object into a class wich have big same other object in some class (similarity) , but its very difference with object in diffrent class (disimilarity). Almost all of clustering algorithm only can solve data with low dimensinality so that result of clustering have less quality. Aubspace clustering is a method to dicided cluster wich built in different subspace so that prefer handling multidimension data to common clustering. Algorithm that implemention subspace clustering such as: COSA, FINDIT, ENCLUS, PROCLUS, CLIQUE, MAFIA, ect.This final project is implemented with MAFIA (Merging of adaptive Finite Intervals). MAFIA is clustering algorithm which use subspace clustering methodby integrity density based and adaptive grid based method so that this algorithm is good enough to handle multidimension data. MAFIA is a density based method due to clustering implementasion based on the density of data that use histogram for analyzing data range on each dimension. This algorithm use bottom-up search to find dense unit depend on the dimension to reduce searching space. Bottom-up use same princip with Apriori algorithm to procused assosoation rule. MAFIA is not need the input number of cluster fund in cluastering so that this algorithm is more fleksible on finding cluster from dataset.Mafia algorithms tested using syntetic dataset. Datasets are generated online at www.datasetgenerator.com. Test results show that MAFIA is good for clustering data multidimensional. Quality is reflected in the maximum accuracy that is equal to that found 0.89.Keyword: clustering, MAFIA algorithm, data mining, subspace clustering