Proper Bit Research Articles

Clinico-pathological study of primary intracranial neoplasms in a tertiary care hospital

Background: Central nervous system neoplasms represent a unique, heterogeneous population of neoplasms and include both benign and malignant tumours. The tumours of central nervous system are reported to be less than 2% of all malignancies. Aim: To study the frequency of intracranial tumours and their histopathological typing and their correlation with several clinical variables such as age, sex and clinical symptoms . Material & Methods: Study Design: Hospital based Prospective observational study. Study area: Dept. of. Pathology, Study Period: 2 years. Study population: patients who presented with signs and symptoms of primary intracranial tumours were examined and followed up for the histopathological diagnosis. Sample size: Study population consisted a total of 68 patients. Sampling method: Simple Random sampling method. Inclusion criteria: Patients with both benign as well as malignant primary neoplasms of the brain including pituitary tumours. Exclusion criteria: All the spinal cord, calvarial and metastatic tumours were excluded. Ethical consideration: Institutional Ethical committee permission was taken prior to the commencement of the study. Study tools and Data collection procedure: Staining Procedures Adopted: After grossing, proper tissue bits were subjected for routine processing, fixation, dehydration, clearing and embedding in paraffin wax and blocks were made.

High Efficiency Rate Control for Versatile Video Coding Based on Composite Cauchy Distribution

In this work, we propose a novel rate control algorithm for Versatile Video Coding (VVC) standard based on its distinct rate-distortion characteristics. By modelling the transform coefficients with the composite Cauchy distribution, higher accuracy compared with traditional distributions has been achieved. Based on the transform coefficient modelling, the theoretically derived R-Q and D-Q models which have been shown to deliver higher accuracy in characterizing RD characteristics for sequences with different content are incorporated into the rate control process. Furthermore, to establish an adaptive bit allocation scheme, the dependency between different levels of frames is modelled by a dependency factor to describe relationship between the reference and to-be-coded frames. Given the derived R-Q and D-Q relationships, as well as the dependency factor, an adaptive bit allocation scheme is developed for optimal bits allocation. We implement the proposed algorithm on VVC Test Model (VTM) 3.0. Experiments show that due to proper bit allocation, for low delay configuration the proposed algorithm can achieve 1.03% BD-Rate saving compared with the default rate control algorithm and 2.96% BD-Rate saving compared with fixed-QP scheme. Moreover, 1.29% BD-Rate saving and higher control accuracy have also been observed under the random access configuration.

ACME-2: Improving the Extraction of Essential Bits in Xilinx SRAM-Based FPGAs

Fault emulation in field-programmable gate arrays (FPGAs) is a popular alternative to test the reliability of a design due to its low cost and high availability compared to traditional radiation-based approaches. Fault emulation is an instrumentation method based on inducing artificial bit flips on the design under test (DUT) to modify the content of its memory elements or the structure of the design itself. A major limitation of error emulation in FPGAs lies in the determination of the proper bits to test, which is directly related to the reliability results obtained and the execution times of the fault injection campaign. The Automatic Configuration Memory Error-injection (ACME) tool helps with this process in Xilinx FPGAs by obtaining the essential bits of an FPGA region where the DUT is. In this paper, we present ACME-2, an improved version of the tool where the translation from the FPGA region to design essential bits has been modified with architectural information of the FPGA. In this revision of the tool, redundant input/output routing bits that distort the reliability results are minimized. For the example designs used in the experiments, these modifications have led to an improvement in the precision of the reliability results as well as a reduction of the fault injection campaign runtime over the previous version of the tool.

Torque Ripple Minimization in Switched Reluctance Motor using ANFIS Controller

An inborn torque swell portrays changed hesitance innovation from traditional innovation. A definitive target of this paper is to minimize the torque wave of the exchanged hesitance engine drive utilizing Artificial Network Fuzzy Inference System based direct torque conspire. In the proposed controller arrange proper bits of information are picked for preparing and testing. The best possible choice of the learning rate and energy will help in weight change. The Intelligent controller gives high power over motor torque and speed, lessens rise time just as overshoot. Here the blunder is decreased which demonstrates that the determination of voltage vectors from the vector table is exact and its outcomes in better torque reaction over a wide scope of speed. The reenactment results uncover that the torque swells fluctuate between 3.75% to 2.25% for the variety in load torque and the drive speed. The experimental results for the proposed controller reveal that the torque ripple varies between 3.9% to 2.4% for the variation in speed. Both the recreation and equipment results delineate the effectiveness of the controller.

DRILL BIT SELECTION IN A FORMATION WITH DIFFERENT SEDIMENTARY FACIES USING THE MARKOV CHAIN: A CASE STUDY AT ONE OF THE OIL FIELDS IN THE SOUTH OF IRAN

The selection of a drill bit is an essential issue in well planning. Furthermore, identification and evaluation of sedimentary rocks before well drilling plays a crucial role in choosing the drill bit. Moreover, the Markov chain as a stochastic model is one of the powerful methods for identifying lithological units, which is based on the calculation of the transition probability matrix or transition matrix. The Markov chain experiences transitions from one state (a situation or set of values) to another according to specified probabilistic rules. In this paper, the Markov chain was implemented for bit selection in a formation with different sedimentary facies (such as the Dashtak Formation). Therefore, the proper drill bit was proposed by utilizing the transition matrix of rock facies and the available bits. This process was carried out in two wells where the thicknesses of the Dashtak Formation are 960 meters and 1410 meters. Consequently, the results indicate that the Markov chain is a practical method for selecting bits in a sequence of rock facies based on an acceptable matching between the reality mode (the used bits in the well) and the Markov chain results. Besides, in the case of using an improper bit in a well, and using a bit in a washing and reaming operation, there were differences between the used bits and the Markov chain outputs.

ÜÇ KONİLİ ROTARİ MATKAPLARIN SEÇİMİNDE DİKKAT EDİLECEK ÖNEMLİ PARAMETRELER

Açık ocak madenciliği delme patlatma işlerinde yaygın olarak kullanılan matkap türlerinden biri de üç konili matkaplardır. Her ne kadar bu matkapların seçiminde genellikle IADC kodları kullanılsa da matkapların delme hızı ve dayanımına birçok parametre etki etmektedir. Günümüzde niteliksiz ürünlerin yaygınlaşmasından dolayı kullanıcılar matkap ömrünü artırmak için yüksek IADC kodlarında seçim yapma eğilimindedir. Bu ise delme hızını düşürmekte ve delme maliyetini artırmaktadır. Matkap seçiminde; öncelikle matkabın üretim aşamasında doğru malzeme kullanılmış ve uygun metalurjik süreçlerden geçmiş olmasına ayrıca matkap tasarımının formasyon şartlarına uygun olup olmadığına dikkat edilmesi gerekmektedir. Kullanım aşamasında ise verimliliği artırmak için baskı kuvveti ve dönme hızı gibi çalışma parametrelerine ait değerler formasyon özelliklerine göre belirlenmelidir. Matkap seçiminde sadece matkap maliyeti değil, bütün olarak delme işlemi maliyeti dikkate alınmalıdır.

Analysis of small holes manufacturing for optomechanical components

Small holes can be manufactured by several ways. It is important to define in what dimensions the small holes vary. Anyway, drilling is one of the oldest technologies of holes manufacturing. In small dimensions we use the term microdrilling for description. Beside this conventional way of manufacture there are also unconventional methods. Microdrilling bits very often break before they are worn. Therefore, the tool life of these bits its quite unexpectable. It is due to relatively high load against the drill bit strength. So, it is important to choose proper drill bit material, cutting geometry, construction, process liquid, clamping and cutting conditions. These parameters are import for achieving ideal conditions for microdrilling. Even a tiny change in pre-seted parameters can lead to destruction of these delicate tools. Fiber arrays are designed and manufactured for precise positioning of optical fibers in row (1D) or in plate (2D). Fiber arrays can contain most of fibers including polarization maintaining fibers (PMF).

A 4‐bit ultra‐wideband complementary metal‐oxide‐semiconductor attenuator with low root‐mean‐square amplitude error

This article presents the 4-bit ultra-wideband complementary metal-oxide-semiconductor (CMOS) attenuator in a standard 0.18-μm CMOS process. This design adopts switched bridge-T type topologies for each attenuation bit. Based on insertion losses and input P1-dB considerations, the circuit performances can be optimized by the proper bit ordering arrangement. Therefore, the bit ordering 0.5-4-2-1 dB is employed in the 4-bit attenuator. Moreover, series inductors are added between each bit to further improve the input and output return losses. Measured results demonstrate that the attenuation range of the circuit is 7.5 dB with 0.5 dB step and the root-mean-square (RMS) amplitude error is between 0.11 and 0.13 dB from 3.1 to 10.8 GHz. The differences between simulated and measured RMS amplitude errors are less than 0.2 dB, which demonstrates the good agreement and feasibility of the design concept. The measured input P1-dB is 15 dBm at 5 GHz and the chip area is 1.12 mm2 including all testing pads.

Flexible-Rate SIC-Free NOMA for Downlink VLC Based on Constellation Partitioning Coding

Visible light communication (VLC) systems utilizing conventional superposition coding/successive interference cancellation (SPC/SIC)-based non-orthogonal multiple access (NOMA) suffer from the error propagation effect due to imperfect SIC. In this letter, we propose a flexible-rate SIC-free NOMA technique for downlink VLC systems, based on constellation partitioning coding (CPC) and uneven constellation demapping (UCD). By using CPC/UCD, SIC is not required and hence error propagation can be eliminated in NOMA-based VLC systems. Moreover, by selecting a proper bit allocation scheme, flexible-rate multiple access can be supported in the VLC system applying CPC/UCD-based NOMA. Proof-of-concept two-user VLC experiments verify that, compared with conventional SPC/SIC-based NOMA, the bit error rate performance of the near user can be greatly improved by using CPC/UCD-based NOMA, and hence the effective power allocation ratio range can be substantially extended.

On the Performance of Cell-Free Massive MIMO With Low-Resolution ADCs

This paper considers an uplink cell-free massive multi-input multi-output (mMIMO) system with multi-antenna access points (APs) and users, assuming low-resolution analog-to-digital converter (ADC) architecture is employed at the APs. Leveraging on the additive quantization noise model (AQNM), we derive a tight approximate expression for uplink spectral efficiency (SE). This trackable finding provides us with a tool for easily quantifying the impacts of the number of antenna arrays and the number of quantization bit of low-resolution ADCs. We find 5-bit is required in a cell-free mMIMO with low-resolution ADCs to achieve the same SE as a cell-free mMIMO with full-precision ADCs. Besides, when the number of antennas of the user is small, deploying more antennas at the users can boost the sum SE. Then, to further highlight the potential of low-resolution ADCs architecture, we also investigate the tradeoff between the SE and energy efficiency (EE) with design issues surrounding the quantization bit of low-resolution ADCs and the number of antenna arrays. The resulting observations reveal that by choosing a proper quantization bit, the cell-free mMIMO with low-resolution ADCs has the capability to enjoy a better SE-EE tradeoff compared to the perfect ADCs counterpart.

Optimum Drill Bit Selection by Using Bit Images and Mathematical Investigation

This study is designed to consider the two important yet often neglected factors, which are factory recommendation and bit features, in optimum bit selection. Image processing techniques have been used to consider the bit features. A mathematical equation, which is derived from a neural network model, is used for drill bit selection to obtain the bit’s maximum penetration rate that corresponds to the optimum parameters for drilling. At the end, the bit with the maximum penetration rate is chosen. The results of this study showed that bit pattern can be inserted in the calculation through a proper bit image processing technique. This is to ensure that each unique bit can be discriminated from other bits. The values of mean square error and coefficient of determination (R2) were respectively found as 0.0037 and 0.9473, for the rate of penetration model. The image processing techniques were used to extract the bit features. The artificial neural network black box was converted to white box in order to extract a mathematical equation and visibility of the model.

Jointly Optimized Reed-Muller Codes for Multi-Level Multi-Relay Coded-Cooperative VANETS

In this paper, we present the well-known Reed–Muller (RM) codes for multilevel multirelay vehicular adhoc networks, which can enjoy coded-cooperation among network nodes. At first, we present the code construction principles for a single node/relay scenario and then extend the design principles to the two-level two-relay and, finally, to multilevel multirelay scenarios. The term “level” refers to the fact that different order RM code is used at each relaying node. Plotkin's construction is exploited to utilize RM codes in such coded-cooperative schemes. To achieve an optimum code at the destination node, proper encoding strategy needs to be employed at the relay node. Therefore, we propose a design criteria and an efficient algorithm for proper bit selection at the relay nodes to achieve the best possible code at the destination. It is observed that the increase in the number of levels as well as relays result in better channel code at the destination, as compared to the lesser number of relays, however, at the cost of increased decoding complexity. The channels considered to analyze the bit error rate (BER) performances of proposed coded-cooperative schemes are fast and slow Rayleigh fading channels. At the destination, soft decision maximum likelihood decoding is employed. Numerical simulations show that the single-relay RM coded-cooperative scheme provides significant BER performance gains over the noncooperative and state-of-the-art distributed turbo coded-cooperative schemes under identical conditions.

Asynchronous Threshold-Based Detection for Quantity-Type-Modulated Molecular Communication Systems

Diffusion-based molecular communication has become a promising scheme for communication between nanoscale devices, and various modulation schemes have recently been proposed, including type, quantity, and concentration modulation. In this paper, a novel approach of using both quantity and type of molecules to convey information is considered. An asynchronous threshold-based detection algorithm, called count-to-a-threshold (CTAT), is proposed and compared to the baseline detection approach of majority-counting (MC), which simply counts and compares the number of each type of molecule received. The MC detection algorithm, although straightforward and simple, cannot deliver satisfactory performance under the diffusion channel due to the randomness of the arriving time of molecules. On the other hand, the proposed CTAT detection, which exploits properties of the diffusion channel, greatly improves the performance of quantity-type-modulated diffusion-based molecular communication systems. Both simulations and theoretical analysis are conducted to confirm the effectiveness of the proposed CTAT detection scheme with and without background noise. Based on the analysis, guidelines to design proper molecule quantities, bit intervals, and block sizes to optimize the CTAT detection system are provided.

Lowering Error Floors of Systematic LDPC Codes Using Data Shortening

In this paper, data shortening methods for lowering error floors of systematic LDPC codes are proposed. Rather than attempting to analyze trapping (or stopping) sets of a given LDPC code rigorously, we search information bits associated with dominant trapping (or stopping) sets of systematic LDPC codes through simulation under various channels. Then, proper information bits forming dominant trapping (or stopping) sets are selected and known values are assigned to them before encoding to weaken the effect of dominant trapping (or stopping) sets. To decode codewords, fixed known values are assigned to the selected information bits, which gives rise to the disconnection of some edges in dominant trapping (or stopping) sets. Through simulation, it is shown that the proposed schemes result in remarkably better performance, especially at the error floor region, than the base LDPC codes under various channels with negligible loss of code rate.

Performance analysis of secure beaconing messages for GeoNetworking

ABSTRACTGeoNetworking is a protocol specially designed to provide geographical addressing and forwarding for Cooperative Intelligent Transport Systems (ITS). Unlike advanced messages defined in GeoNetworking, beaconing messages are fundamental to periodically advertise essential information, e.g., a vehicle ITS station's geographical position and speed, to neighbor ITS stations. The beaconing messages should be delivered in a secure manner. Otherwise, geographical addressing and forwarding of GeoNetworking cannot be supported as unauthorized actions from attackers break down cooperative communication between ITS stations. However, security mechanisms for beaconing messages come with overhead that affect the overall performance. This being so, in this paper, we analyze the overhead of secure beaconing messages in terms of packet delivery ratio, delay, and normalized throughput. From the conducted numerical analysis, we demonstrate that 1) three parameters such as the number of ITS stations in a given radio range, the backoff window size, and the message size mainly affect the performance; 2) the delay of secure beaconing message is still acceptable with proper channel bit rates; and 3) the normalized throughput of secure beaconing message is better than that of the basic beaconing message. Copyright © 2011 John Wiley & Sons, Ltd.

Bit Selection Optimization Using Artificial Intelligence Systems

Optimizing bit selection is one of the main challenges in drilling operations. Bit selection is based on the recorded performance of similar bits from offset wells. There are too many parameters intervening in drilling bit selection. Therefore, developing a logical relationship between them to assist in proper bit selection is extremely necessary and complicated though. In such a case, artificial neural networks (ANNs) have proven to be helpful in recognizing the complex relationship between variables. In this new approach, two models are developed with high proficiency using ANNs. The first model provides appropriate drilling bit selection based on the desired rate of penetration (ROP) to be obtained by applying specific drilling parameters. The second model uses proper drilling parameters obtained from an optimizing procedure to select the drilling bit that provides the maximum achievable rate of penetration. Genetic algorithms (GAs), as a class of optimizing methods for complex functions, are applied to help bit optimization and its related drilling parameters. With the given data sets, these new models predicted successfully the bit types and the optimum drilling parameters. The correlation coefficients for the predicted bit types and optimum drilling parameters in testing the obtained networks are 0.96 and 0.86, respectively. MATLAB software was used to perform ANN and GA solutions.

Feedback-free rate-allocation scheme for transform domain Wyner–Ziv video coding

In most existing Wyner---Ziv video coding schemes, a feedback channel (FC) is expected at the decoder in order to allocate a proper bit rate for each Wyner---Ziv frame. However, FC not only results in additional latency but also increases decoding complexity due to the several feedback-decoding iterations. Moreover, FC may be unavailable in many practical video applications. In this paper, we propose a novel feedback-free rate-allocation scheme for transform domain Wyner---Ziv video coding (TD-WZVC), which predicts the rate for each Wyner---Ziv frame at the encoder without significantly increasing the complexity of the encoder. First, a correlation estimation model is presented to characterize the relationship between the source frame and the reference frame estimated at the encoder in TD-WZVC. Then, an efficient FC-free rate-allocation algorithm is proposed and a linear model is built to avoid both overestimation and underestimation of the real rate and obtain an optimal rate-distortion performance. Experimental results show that the proposed scheme is able to achieve a good encoder rate allocation while still maintaining consistent coding efficiency.

An Intra-Frame Rate Control Algorithm for Ultralow Delay H.264/Advanced Video Coding (AVC)

This paper presents an intra-fame rate control algorithm for ultralow delay H.264/AVC coding. The main goal of the proposed scheme is to allocate a proper bit budget to each macroblock (MB), based on its complexity (or activity). However, since a coder needs to start encoding a frame before buffering the whole frame for very low delay video streaming applications, the relative complexity of each MB can not be known in advance. So, the proposed algorithm predicts a relative complexity of a current MB from complexities of its spatially/temporally neighboring MBs, and then allocates a proper bit budget to the MB using the predicted complexity. Finally, quantization parameter of each MB is obtained by comparing the generated bits and allocated bit budget, and is refined for improving coding performance, based on information from the previous frame. Even though the required buffer size is only around one-third of average bits per a frame in order to achieve very low coding delay, the proposed algorithm provides reliable coding performance compared to the conventional schemes. Simulation results show that the proposed algorithm can prevent the buffer overflow or underflow and it provides better coding performance.

A Novel Approach for Joint Radio Resource Management Based on Fuzzy Neural Methodology

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> In this paper, an innovative mechanism to perform joint radio resource management (JRRM) in the context of heterogeneous radio access networks is introduced. In particular, a fuzzy neural algorithm that is able to ensure certain quality-of-service (QoS) constraints in a multicell scenario deployment with three different radio access technologies (RATs), namely, the wireless local area network (WLAN), the universal mobile telecommunication system (UMTS), and the global system for mobile communications (GSM)/Enhanced Data rates for GSM Evolution (EDGE) radio access network (GERAN), is discussed. The proposed fuzzy neural JRRM algorithm is able to jointly manage the common available radio resources operating in two steps. The first step selects a suitable combination of cells built around the three available RATs, while the second step chooses the most appropriate RAT to which a user should be attached. A proper granted bit rate is also selected for each user in the second step. Different implementations are presented and compared, showing that the envisaged fuzzy neural methodology framework, which is able to cope with the complexities and uncertainties of heterogeneous scenarios, could be a promising choice. Furthermore, simulation results show that the reinforcement learning mechanisms introduced in the proposed JRRM methodology allow guaranteeing the QoS requirement in terms of the so-called user dissatisfaction probability in the presence of different traffic loads and under different dynamic situations. Also, the proposed framework is able to take into consideration different operator policies as well as different subjective criteria by means of a multiple decision-making mechanism, such as balancing the traffic among the RATs or giving more priority to the selection of one RAT in front of another one. </para>

A Novel 4-D Perceptual Quantization Modeling for H.264 Bit-Rate Control

Bit-rate control plays a major role In video coding and multimedia streaming. A well-designed bit-rate control mechanism can achieve line visual qualities and avoid network congestion over a time-varying channel. This paper proposes an H.264 bit-rate control using a 4D perceptual quantization modeling (PQrc), including two major encoding modules: the perceptual frame-level bit-allocation using a 1D temporal pattern and the macroblock-level quantizer decision using a 3D rate pattern. The temporal pattern is used to predict frame complexity and determine proper budget bits further. The rate pattern is depicted as a bit-complexity-quantization (B.C.Q.) model, in which a tangent slope of a B.C.Q. curve is a piece of unique information to find a proper quantizer. For newly generated video clips, the B.C.Q. model is updated continuously using a weighted least-square estimation. In comparison with the latest H.264 JM10.2, our experiment results show that the proposed PQrc can: 1) keep stable buffer fullness and 2) improve the SNR quality and control accuracy effectively.