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There is a rapid increase in online social networks (OSN) due to the development of information and communication technologies (ICT). People around the globe are adopting the new OSN to keep in touch with friends and family members, to remain updated with the latest trends and news, etc. In almost every OSN, few influential users are active and attract other members and make clusters. Many users connect with these influential users to remain in touch with the latest ongoing trends as the influential nodes come up with the latest news. In this work, the structural analysis of the Facebook network is undergone. The influential nodes have been identified based on betweenness centrality (BC) and degree centrality (DC) measures. Further, community detection has been made in the whole network especially around the influential nodes. Upon filtration of four top-ranked nodes selected based on the high value of BC and DC, only 22.75% nodes and 8.87% remain in the network. Hence, there is a big question about the sustainability of OSN.

The dream towards fully autonomous vehicles brings a lot of challenges in terms of reliability, high performance computing and sensing capabilities in a vehicle. Nowadays, autonomous vehicles are equipped with several sensors, which allow the vehicle to sense everything on the road and to collect the information needed to drive safely. Altogether, these sensors generate a lot of data, roughly 4TB in a single day [1]. In order to process this abundance of sensory data faster and reliably, there is a need for high performance microcontroller units (MCUs) and fault tolerant data processing respectively. For this reason, we have developed a smart reconfigurable sensor (SRS) platform, which aims to solve the challenges of high performance computing and safety. An in-house fabricated entire silicon-based millimeter-wave transceiver, using IHP's 130 nm SiGe BiCMOS technology, is used as SRS front-end and software (SW) based triple modular redundancy (TMR) system is implemented for fault tolerant radar data processing. Our highly adaptive system supports fault tolerant modes (i.e. fail operational, fail safe), low power mode and distributed execution of tasks among different cores, all while meeting the strict automotive standards.

The ambitious goals for implementing autonomous systems in nearly all industry sectors create big challenges for the designers of such devices. Especially sensors, key factors for enabling autonomy, must fulfil greatest demands. The challenge is to build highly reliable sensory systems, preferably based on commercial off-the-shelf components, with short design cycles, high robustness against faults and minimal power consumption. In this paper, we present an approach for designing such a sensory system that targets automated driving. Designed as a configurable software-implemented TMR system, we based it on three Tensilica Fusion G3 cores with negligible additional hardware to each core. We are able to show that this system can be controlled to support low power, fail safe, fail operational and distributed execution of different tasks, all while keeping the strict timing and safety constraints that are crucial in the automotive area.

In networked control systems, transmitted data should be quantized into a relatively small number of bits if the rate of the communication channel is not sufficiently high. We propose a feedback quantizer for an implementable simple quantizer with high precision for networked control. The infinite impulse response (IIR) feedback filter is designed to mitigate the effect of the quantization error under a performance constraint of the feedback control system. Then, the minimum rate that achieves the constraint is numerically obtained. Simulations are provided to show the effectiveness of the proposed quantizer in a networked feedback control system.

The economy being highly based on agriculture demands innovative and reliable methods of irrigation. The shortcomings of manual methods of irrigation can be rectified using automated process. This paper presents the idea of automatic irrigation method and the following research sustains this idea. The task of automatic irrigation is done through assistance of soil moisture sensors. In the project, apart from soil moisture sensor. Humidity and temperature sensors are also used to make the process more advance. The proposed design also has the feature of GSM which makes this system wireless. The electricity required by components is provided through solar panels hence this liberates us from interrupted power supply due to load shedding. The water content is constantly judged and whenever moisture level of soil gets low, the system sends a signal to motors asking them to turn on. The motors automatically stop after soil reaches its maximum upper threshold value which is decided by user. Every time the motor starts or stops automatically, the user will get a SMS about the status of operation. The major advantages of the project include avoidance from water wastage, growth of plants to their maximum potential, less chances of error due to less labor and uninterrupted supply of water due to solar energy.

In this paper, we propose two types of noise shaping infinite impulse response (IIR) filters for ΔΣ modulators based on H2 and H∞ norms of the in-band quantization noise. We utilize the hybrid-design and the least-squares approximation method to obtain noise shaping IIR filters by taking an indirect approach for solving the non-convex optimization problem. In both methods, we also incorporate the non-ideal behavior of the output lowpass filter into the design criteria of our noise shaping IIR filter as a weighting function. To demonstrate the effectiveness of proposed noise shaping IIR filters, we compare it with existing design methods.

Delta-Sigma modulators are often utilized to convert analog signals into digital signals. The quantization error of a Delta-Sigma modulator can be reduced by oversampling. However, oversampling increases the number of bits per time if the same number of bits are assigned to each output of the quantizer. Due to limited bandwidth, the rate-distortion relation is necessary to balance the rate and the distortion. In this paper, we analyze the relationship between the rate and the distortion of an optimal scalar Delta-Sigma modulator that minimizes the variance of the error in the output of the system connected to the Delta-Sigma modulator. Numerical examples are provided to show rate-distortion relations of the optimal Delta-Sigma modulators.