Coaxial‐fed high‐gain triple‐band zeroth‐order circularly polarized antenna using pseudo‐open termination and asymmetric unit cells

A coaxial‐fed tri‐band zeroth‐order resonance (ZOR) circularly polarized antenna with higher gains for all the excited ZORs is designed and analyzed in this paper. Epsilon negative transmission line (ENG TL) and pseudo‐open termination (P‐OT) unit cells with different series capacitances (C_S and C_S1 ) resonate shunt ZOR (f_sh ) and two series ZORs (f_se and f_se1 ), respectively. Asymmetric unit cell concept is applied to ENG‐TL and P‐OT unit cells to create vertical and horizontal components, and the 90° phase shift is provided by the ZOR, resulting in circular polarization (CP). Left‐hand CP (LHCP) is achieved by creating two 90° right bends to the extended stubs in ENG TL and P‐OT unit cells. Higher gains for all the excited ZORs are achieved by shifting the shorting pins of ENG TL and P‐OT unit cells far away from the center position. After fabrication, the measured resonances occur at 4.64 GHz (f_sh ), 4.04 GHz (f_se ), and 3.86 GHz (f_se1 ) with fractional bandwidths of 1.62%, 1.73%, and 1.6%, respectively. The measured LHCP peak gains are 4.05 dBic (f_sh ), 3.85 dBic (f_se ), and 3.94 dBic (f_se1 ). The average axial ratio obtained is less than 3‐dB in the 10‐dB fractional bandwidth of the proposed antenna.     

Passenger flow prediction in bus transportation system using deep learning

The forecasting of bus passenger flow is important to the bus transit system’s operation. Because of the complicated structure of the bus operation system, it’s difficult to explain how passengers travel along different routes. Due to the huge number of passengers at the bus stop, bus delays, and irregularity, people are experiencing difficulties of using buses nowadays. It is important to determine the passenger flow in each station, and the transportation department may utilize this information to schedule buses for each region. In Our proposed system we are using an approach called the deep learning method with long short-term memory, recurrent neural network, and greedy layer-wise algorithm are used to predict the Karnataka State Road Transport Corporation (KSRTC) passenger flow. In the dataset, some of the parameters are considered for prediction are bus id, bus type, source, destination, passenger count, slot number, and revenue These parameters are processed in a greedy layer-wise algorithm to make it has cluster data into regions after cluster data move to the long short-term memory model to remove redundant data in the obtained data and recurrent neural network it gives the prediction result based on the iteration factors of the data. These algorithms are more accurate in predicting bus passengers. This technique handles the problem of passenger flow forecasting in Karnataka State Road Transport Corporation Bus Rapid Transit (KSRTCBRT) transportation, and the framework provides resource planning and revenue estimation predictions for the KSRTCBRT.

     

Efficient Beamformer for Low Mobility Indoor Communication Using Sparse Adaptive Algorithm

Wireless Personal Communications - The proposed beamforming model exploits the underlying sparseness of the adaptive filter as impulse response of wireless channel shows some extent of sparse...     

Frequency tunable low ripple and fast response on-chip DC–DC converter for DVFS

Dynamic voltage and frequency scaling (DVFS) is an efficient method to reduce the power consumption in system on-chip. To support DVFS, multiple supply voltages are generated based on different work load frequencies and currents using on-chip DC–DC voltage converter. In this paper a frequency tunable multiple output voltage switched capacitor based dc–dc converter is presented. An analog to digital converter and phase controller is used in the feedback to change the switching frequency and duty cycle of the converter. An input voltage of 1.8 V is converted to 0.6 and 0.8 V for low and high signal frequency respectively. The proposed 2-phase switched capacitor architecture with gain setting of 1:2 is designed with the 90 nm technology. An output ripple of 45 mV is observed and the maximum transient response time of the converter is 17.3 ns (= 58 MHz).     

Design of a broadband highly dispersive pure silica photonic crystal fiber

A highly dispersive dual-concentric-core pure silica photonic crystal fiber is designed with a maximum chromatic dispersion value of about -9500 ps/(nm km) around the 1.56 microm wavelength region and a full width at half-maximum (FWHM) of 55 nm. The change in the dispersion-bandwidth product as a function of period is carefully studied by using the plane wave expansion method. The coupled mode theory matches well with the plane wave expansion method that was used to simulate the chromatic dispersion. This kind of a photonic crystal fiber structure is suitable for high-dispersion application in phased array antenna systems based on photonic crystal fiber arrays.     

A single-phase algorithm for mining high utility itemsets using compressed tree structures

Mining high utility itemsets (HUIs) from transaction databases considers such factors as the unit profit and quantity of purchased items. Two-phase tree-based algorithms transform a database into compressed tree structures and generate candidate patterns through a recursive pattern-growth procedure. This procedure requires a lot of memory and time to construct conditional pattern trees. To address this issue, this study employs two compressed tree structures, namely, Utility Count Tree and String Utility Tree, to enumerate valid patterns and thus promote fast utility computation. Furthermore, the study presents an algorithm called single-phase utility computation (SPUC) that leverages these two tree structures to mine HUIs in a single phase by incorporating novel pruning strategies. Experiments conducted on both real and synthetic datasets demonstrate the superior performance of SPUC compared with IHUP, UP-Growth, and UP-Growth+ algorithms.     

Fully integrated 1.2-μA and 13-μA quiescent current LDOs with improved transient response

We introduce two extremely low quiescent current (I _Q ) low-dropout (LDO) voltage regulators. The Low I _Q -LDO (LI _Q -LDO) uses 13 μA of total quiescent current and is designed for a maximum load current of 50 mA. The Micro I _Q -LDO (MI _Q -LDO) uses only 1.2 μA of total quiescent current and is designed for a maximum load current of 5 mA. Detailed pole/zero analysis is performed to aid in the design of the LDOs. Two LHP zeros cancel the two non-dominant poles which extend the bandwidth and improve transient response. Both designs are fully integrated, stabilized with an on-chip capacitive load of 100 pF. In load transient, the total variation in output voltage for LI _Q -LDO and MI _Q -LDO is 1 V and 950 mV, respectively, and the total line transient variation is 668 and 599 mV, respectively. Both designs occupy an area of 0.26 mm² in a 0.5-μm CMOS process. Two process-independent figures of merit are proposed to compare LI _Q -LDO and MI _Q -LDO with other published work.