Design and analysis of a novel low PDP full adder cell

This paper, presents a new full-swing low power high performance full adder circuit in CMOS technology. It benefits from a full swing XOR-XNOR module with no feedback transistors, which decreases delay and power consumption. In addition, high driving capability of COUT module and low PDP design of SUM module contribute to more PDP reduction in cascaded mode. In order to have accurate analysis, the new circuit along with several well-known full adders from literature have been modeled and compared with CADENCE. Comparison consists of power consumption, performance, PDP, and area. Results show that there are improvements in both power consumption and performance. This design trades area with low PDP

FARS: Fuzzy Ant based Recommender System for Web Users

Recommender systems are useful tools which provide an adaptive web environment for web users. Nowadays, having a user friendly website is a big challenge in e-commerce technology. In this paper, applying the benefits of both collaborative and content based filtering techniques is proposed by presenting a fuzzy recommender system based on collaborative behavior of ants (FARS). FARS works in two phases: modeling and recommendation. First, user’s behaviors are modeled offline and the results are used in second phase for online recommendation. Fuzzy techniques provide the possibility of capturing uncertainty among user interests and ant based algorithms provides us with optimal solutions. The performance of FARS is evaluated using log files of “Information and Communication Technology Center” of Isfahan municipality in Iran and compared with ant based recommender system (ARS). The results shown are promising and proved that integrating fuzzy Ant approach provides us with more functional and robust recommendations

Pengaruh Metode Problem Solving Secara Algoritmik Dan Heuristik Terhadap Prestasi Belajar Ditinjau Dari Kemampuan Metakognisi Siswa Pada Materi Kelarutan Dan Hasil Kali Kelarutan Kelas XI Mia Di SMA N 5 Surakarta

Penelitian ini bertujuan untuk mengetahui: (1) pengaruh metode problem solving secara algoritmik dan heuristik terhadap prestasi belajar siswa materi kelarutan dan hasil kelarutan; (2) pengaruh kemampuan metakognisi terhadap prestasi belajar siswa materi kelarutan dan hasil kelarutan; (3) interaksi antara metode problem solving secara algoritmik dan heuristik dengan kemampuan metakognisi terhadap prestasi belajar siswa materi kelarutan dan hasil kelarutan. Penelitian ini menggunakan metode eksperimen dengan desain faktorial 2x2. Sampel penelitian ini adalah kelas XI MIA 3 dikenai metode problem solving secara algoritmik dan kelas XI MIA 4 dikenai metode problem solving secara heuristik yang diambil dengan teknik cluster random sampling. Analisis data penelitian ini menggunakan analisis variansi dua jalan dengan sel tak sama dan uji statistik non parametrik Kruskal Wallis H. Hasil penelitian menunjukkan bahwa: (1) ada pengaruh metode problem solving secara algoritmik dan heuristik terhadap prestasi aspek pengetahuan, sedangkan pada prestasi aspek sikap dan keterampilan tidak ada pengaruh metode pembelajaran terhadap prestasi belajar siswa; (2) tidak ada pengaruh kemampuan metakognisi terhadap prestasi aspek pengetahuan, sikap, maupun keterampilan siswa; (3) tidak ada interaksi antara metode problem solving secara algoritmik dan heuristik dengan kemampuan metakognisi terhadap prestasi aspek pengetahuan, sikap, dan keterampilan siswa

Pengaruh Pintu Keluar Mall Bumi Kedaton Dan U Turn Sebelum Lintas Jalan Rel Di Jalan Sulta Agung (Studi Kasus Simpang Jl. Teuku Umar – Jl. ZA. Pagar Alam – Jl. Sultan Agung)

This research used primary data and secondary data. The primary data is obtained from the directsurvey result in the form of geometry data, environmental condition data, traffic flow, signaltiming, and long queues. Secondary data consists of the population in Bandar Lampungat 2012that is get from BPS Lampung Province. Data analysis is used the Indonesian Manual HighwayCapacity in 1997 for Signalized Intersections. Based on calculations, it can found that theintersection level of service at aftrenoon peak hour was F with a delay amount 61,50sec/pcu, levelof service at evening peak hour was F with a delay amount 88, 20sec/pcu, and level of service atnight peak hour was F with a delay amount 60, 29sec/pcu. Similarly, with the U Turn result canobtained the intersection level of service at afternoon peak hour was B, level of service at eveningpeak hour was B, and level of service at night peak hour was A.It indicates that the performance ofintersectionis not optimal. To increase the performance of the intersection, need make a changesin the pattern of setting time control become the pattern of not setting time control based on thepeak condition by changing the cycle time, green time, and inter green time. And therecommendation needed for the handling of openings U Turn on Jl. Sultan Agung

Characteristics of alpha projectile fragments emission in interaction of nuclei with emulsion

The properties of the relativistic alpha fragments produced in interactions of 84^Kr at around 1 A GeV in nuclear emulsion are investigated. The experimental results are compared with the similar results obtained from various projectiles with emulsion interactions at different energies. The total, partial nuclear cross-sections and production rates of alpha fragmentation channels in relativistic nucleus-nucleus collisions and their dependence on the mass number and initial energy of the incident projectile nucleus are investigated. The yields of multiple alpha fragments emitted from the interactions of projectile nuclei with the nuclei of light, medium and heavy target groups of emulsion-detector are discussed and they indicate that the projectile-breakup mechanism seems to be free from the target mass number. It is found that the multiplicity distributions of alpha fragments are well described by the Koba-Nielsen-Olesen (KNO) scaling presentation. The mean multiplicities of the freshly produced newly created charged secondary particles, normally known as shower and secondary particles associated with target in the events where the emission of alpha fragments were accompanied by heavy projectile fragments having Z value larger than 4 seem to be constant as the alpha fragments multiplicity increases, and exhibit a behavior independent of the alpha fragments multiplicity.Comment: 33 pages, 8 figures and 3 tables (in press

Detecting and Estimating Magnetic Fluid Properties by a Needle- Type GMR Sensor

Magnetic fluid or magnetic liquid are colloidal solutions of ultra-fine magnetic materials. Ferromagnet-ic materials consist of magnetic or other compound containing iron, nickel or cobalt, by a particle size of 5 to 50 nanometers, generally in a superparamagnetic, ferromagnetic or diamagnetic state. Magnetic fluids have a unique combination of strength and ability to interact with the magnetic field. This paper proposes to estimate and detect magnetic fluid weight density (concentration as low as 1%) by giant magnetore-sistance (GMR) sensor. The high sensitivity of the sensor is around 11 μV/μT. We propose to use it for bio-applications to characterize magnetic microfluides. For this application a Helmholtz coil was simulated and fabricated to make more uniform magnetic flux density. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/3496

Data-efficient performance learning for configurable systems

Many software systems today are configurable, offering customization of functionality by feature selection. Understanding how performance varies in terms of feature selection is key for selecting appropriate configurations that meet a set of given requirements. Due to a huge configuration space and the possibly high cost of performance measurement, it is usually not feasible to explore the entire configuration space of a configurable system exhaustively. It is thus a major challenge to accurately predict performance based on a small sample of measured system variants. To address this challenge, we propose a data-efficient learning approach, called DECART, that combines several techniques of machine learning and statistics for performance prediction of configurable systems. DECART builds, validates, and determines a prediction model based on an available sample of measured system variants. Empirical results on 10 real-world configurable systems demonstrate the effectiveness and practicality of DECART. In particular, DECART achieves a prediction accuracy of 90% or higher based on a small sample, whose size is linear in the number of features. In addition, we propose a sample quality metric and introduce a quantitative analysis of the quality of a sample for performance prediction

Evolutionary Computation in Coded Communications: an Implementation of Viterbi Algorithm

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A Communicative Landscape of Health Information Needs for Malaria Management in the Millennium Villages Project in Bonsaaso, Ghana

We performed a qualitative study (n=39) mapping the health information needs of stakeholders involved with malaria prevention and treatment in rural Ghana as part of a larger effort to develop integrated, scalable eHealth tools. Initial results can be categorized into four areas: health care delivery, data quality, technical problems and workforce-related problems. This comprehensive review of information challenges in one area identifies fertile ground for potential improvement using health information technology