To keep supporting next-generation requirements, the radio access infrastructure will increasingly densify. Cell-free (CF) network architectures are emerging, combining dense deployments with extreme flexibility in allocating resources to users. In parallel, the Open Radio Access Networks (O-RAN) paradigm is transforming RAN towards an open, intelligent, virtualized, and fully interoperable architecture. This paradigm brings the needed flexibility and intelligent control opportunities for CF networking. In this paper, we document the current O-RAN terminology and contrast it with some common CF processing approaches. We then discuss the main O-RAN innovations and research challenges that remain to be solved.

This manuscript was accepted for publication on IEEE Transactions on Geoscience and Remote Sensing. Abstract: In radar polarimetry, incoherent target decomposition techniques help extract scattering information from polarimetric SAR data. This is achieved either by fitting appropriate scattering models or by optimizing the received wave intensity through the diagonalization of the coherency (or covariance) matrix. As such, the received wave information depends on the received antenna configuration. Additionally, a polarimetric descriptor that is independent of the received antenna configuration might provide additional information which is missed by the individual elements of the coherency matrix. This implies that existing target characterization techniques might neglect this information. In this regard, we suitably utilize the 2D and 3D Barakat degree of polarization which is independent of the received antenna configuration to obtain distinct polarimetric information for target characterization. In this study, we introduce new roll-invariant scattering-type parameters for both full-polarimetric (FP) and compact-polarimetric (CP) SAR data. These new parameters jointly use the information of the 2D and 3D Barakat degree of polarization and the elements of the coherency (or covariance) matrix. We use these new scattering type parameters, which provide equivalent information as the Cloude alpha for FP SAR data and the ellipticity parameter chi for CP SAR data, to characterize various targets adequately. Additionally, we appropriately utilize these new scattering-type parameters to obtain unique non-model based three-component scattering power decomposition techniques. We obtain the even-bounce, and the odd-bounce scattering powers by modulating the total polarized power by a proper geometrical factor derived using the new scattering-type parameters for FP and CP SAR data. The diffused scattering power is obtained as the depolarized fraction of the total power. Moreover, due to the nature of its formulation, the decomposition scattering powers are nonnegative and roll-invariant while the total power is conserved. The proposed method is both qualitatively and quantitatively assessed utilizing the L-band ALOS-2 and C-band Radarsat-2 FP and the associated simulated CP SAR data.

This paper presents a comprehensive three-bus equivalent circuit model of three-phase step voltage regulators. The proposed model can be efficiently integrated in the Z-bus power flow method and can accurately simulate any configuration of step voltage regulators. In contrast to the conventional step voltage regulator models that include the tap variables inside the YBUS matrix of the network, the proposed model simulates them in the form of current sources, outside the YBUS matrix. As a result, the re-factorization of the YBUS matrix is avoided after every tap change reducing significantly the computational burden of the power flow. Furthermore, possible convergence issues caused by the low impedance of step voltage regulators are addressed by introducing fictitious impedances, without, however, affecting the accuracy of the model. The results of the proposed step voltage regulator model are compared against well-known commercial softwares such as Simulink and OpenDSS using the IEEE 4-Bus and an 8-Bus network. According to the simulations, the proposed model outputs almost identical results with Simulink and OpenDSS confirming its high accuracy. Furthermore, the proposed 3-bus equivalent model is compared against a recently published conventional step voltage regulator model in the IEEE 8500-Node test feeder. Simulation results indicate that the proposed step voltage regulator model produces as accurate results as the conventional one, while its computation time is significantly lower. More specifically, in the large IEEE 8500-node network consisting of four SVRs, the proposed model can reduce the computation time of power flow around one minute for every tap variation. Therefore, the proposed step voltage regulator model can constitute an efficient simulation tool in applications where subsequent tap variations are required.

The general diode equation or the non-ideal diode equation is the foundation of circuit models of active devices for the past several decades. Apart from the effect of p-n junction, this equation also accounts for the series bulk resistance of a diode. Despite a reasonable agreement of the equation with measured IV characteristics, it is shown here that the equation is incompatible with basic theories of circuits and systems. Therefore, a modification in the equation is proposed to remove this incompatibility. This modified equation leads to a compact model of a p-n junction diode that has an excellent agreement with the measured IV characteristics.

The Terahertz (THz) band (0.3-3.0 THz), spans a great portion of the Radio Frequency (RF) spectrum that is mostly unoccupied and unregulated. It is a potential candidate for application in Sixth-Generation (6G) wireless networks, as it has the capabilities of satisfying the high data rate and capacity requirements of future wireless communication systems. Profound knowledge of the propagation channel is crucial in communication systems design, which nonetheless is still at its infancy, as channel modeling at THz frequencies has been mostly limited to characterizing fixed Point-to-Point (PtP) scenarios up to 300 GHz. Provided the technology matures enough and models adapt to the distinctive characteristics of the THz wave, future wireless communication systems will enable a plethora of new use cases and applications to be realized, in addition to delivering higher spectral efficiencies that would ultimately enhance the Quality-of-Service (QoS) to the end user. In this paper, we provide an insight into THz channel propagation characteristics, measurement capabilities, and modeling techniques for 6G communication applications, along with guidelines and recommendations that will aid future characterization efforts in the THz band. We survey the most recent and important measurement campaigns and modeling efforts found in literature, based on the use cases and system requirements identified. Finally, we discuss the challenges and limitations of measurement and modeling at such high frequencies and contemplate the future research outlook toward realizing the 6G vision.

Since electron has been discovered, people have been thinking it possess one electric charge, the nuclear possess contrary charge. Based on the provided new discovery that moving photons do create force, I have calculated the number Z of elements, discovered that the number Z of elements can be calculated by frequency of x-ray, and the atomic weight can also be calculated by frequency of x-ray. This method of calculated way shows the essence of electric charge, and shows the essence of gravitational mass, from this way, here in first time provide one way show the unification of gravitation and electromagnetic force.

A mathematical model of a high-sensitivity pressure sensor with a novel electrical circuit utilizing piezosensitive transistor differential amplifier with negative feedback loop (PDA-NFL) is presented. Circuits utilizing differential transistor amplifiers based on vertical n-p-n and lateral p-n-p transistors are analyzed and optimized for sensitivity to pressure and stability of output signal in operating temperature range. Parameters of fabrication process necessary for modeling of I-V characteristics of transistors are discussed. The results of the model are sufficiently close to the experimental data.

Predictive modeling involving brain morphological features and other covariates is of paramount interest in such heterogeneous mental disorders as PTSD. We propose a comprehensive shape analysis framework representing brain substructures, such as the hippocampus, amygdala, and putamen, as parameterized surfaces and quantifying their shape differences using an elastic shape metric. Under this metric, we compute shape summaries (mean, covariance, PCA) of subcortical data and represent individual shapes by their principal scores under a shape PCA basis. These representations are rich enough to allow visualizations of full 3D structures and help understand localized changes. Subsequently, we use these PCs, the auxiliary exposure variables, and their interactions for regression modeling and prediction. We apply our method to data from the Grady Trauma Project (GTP), where the goal is to predict clinical measures of PTSD. The framework seamlessly integrates accurate morphological features and other clinical covariates to yield superior predictive performance when modeling PTSD outcomes. This approach reveals considerably greater predictive power under the elastic shape analysis than the current approaches and helps identify local deformations in brain shapes associated with PTSD severity.

Food safety is an important issue in today’s world. Traditional agri-food production system doesn’t offer easy traceability of the produce at any point of the supply chain, and hence, during a food-borne outbreak, it is very difficult to sift through food production data to track produce and origin of the outbreak. In recent years, blockchain based food production system has resolved this challenge, however, none of the proposed methodologies makes the food production data easily accessible, traceable and verifiable by consumers or producers using mobile/edge devices. In this paper, we propose FoodSQRBlock (Food Safety Quick Response Block), a blockchain technology based framework, which digitizes the food production information, and makes it easily accessible, traceable and verifiable by the consumers and producers by using QR codes. We also propose a large scale integration of FoodSQRBlock in the cloud to show the feasibility and scalability of the framework, and experimental evaluation to prove that.

The advancement of Artificial Intelligence & Deep Learning has catalyzed the field of technology. The progression in these fields is exponentially increasing, and the discoveries which were once just an imagination are now changed into reality. The evolution of cars each year has made a lot of difference in people travelling from one place to another. One such reform involving Artificial Intelligence & Deep Learning is the birth of a self-driving car. The future is here where one can reach their destination hassle-free safely without the fear of accidents. This paper introduces a practical model of the self-driving robotics car, which can travel from one position to another on different types of tracks. A Pi-camera module is attached with the help of Raspberry Pi, which sends series of image frames to the Convolutional neural network, which then foretells the car to move in a specific direction, i.e. right, left, forward and reverse direction. The outcome is the robotics car, which travels in the desired direction without any individual effort.

It is about developing a app which related to second-hand trade among school people.

A novel two-electrode, frequency-scan electrical impedance tomography (EIT) system for gesture recognition not only reduces the measurement complexity and the number of electrodes, but also achieves a high accuracy in recognizing common gestures and pinch gestures. A bespoke circuit with two medical electrodes was developed to collect data from the back of the hand and presented a frequency-scan method to increase the diversity of impedance data. The data were processed using data cleaning and feature extraction methods. The processed data were then sent to machine learning classification models for training and realizing accurate gesture recognition. To verify the effectiveness of this system, we designed two groups of nine gestures in a hand-gesture recognition experiment. The results showed that the system can achieve a recognition accuracy of 98.3% with a group of four common gestures and an accuracy of 97.4% with a group of five pinch gestures. Additionally, two proof-of-concept interactive scenarios were implemented to demonstrate the general purpose of this system.

GatePass Generation and Management System is a software mobile application. The Project “Gate Pass Generation and Management System” is itself tells that is to generate gate pass for regular and for visitor, students, teachers, employees and customers. It maintains the record of visitor and various activities of the user in the system. This can be used to replace our manual visitor process and then give them passes and management process through our system. Gate pass Generation and Management system is available for use of various visitor, students, teachers, employees and customers and it is easy to use and manage. This system is defined as a security system. It’s main aim to secure colleges from outside visitors, the department and the various working institute. Gate pass Generation and management system help the organization as well as a visitor to manage the Gate passes through QR code generator in easy way

Multi Stage Kalman Filter (MSKF) Based Time-Varying Sparse Channel Estimation with Fast Convergence Submitted to IEEE Journal

This paper proposes a new clock offset estimation that mitigates unwanted link asymmetry for precise clock synchronization. The main contribution is to address the design issue of the IEEE 1588 standard precision time protocol (PTP), which estimates clock offset under the assumption that the delays of exchanged packets are symmetric. To mitigate the issue, we focus on the fact that PTP measures asymmetry variation through the derivatives of its timestamps with respect to the time step. By exploiting the measurement of the variation, the proposed approach defines the asymmetry in the form of a linear differential equation (LDE) and leverages the LDE to define and exclude asymmetry-induced errors. Additionally, we clearly derive the state transition of the asymmetry. Subsequently, we derive a novel state-space model from our approach. The model describes PTP clock offset estimation perfectly, allowing optimal clock offset estimation. We verify the theoretical validity of the proposed method with real data. Our approach improves PTP accuracy by more than thousand times and achieves an accuracy at the level of tens to hundreds of nanoseconds on an asymmetric communication link. Our approach realizes an accuracy comparable to that of PTPv2, without the cost of specialized hardware.

This study provides a novel mechanical design and a control law for tendon-driven flexible manipulator based on the anatomy of an ostrich neck. We carried out a dissection of ostrich neck which clarified muscle attachment site and cross-sectional views of the neck. We proposed a novel wire arrangement and control method, that performs the same movement as the ostrich's neck by integrating our findings from the dissection with previous studies on bird's necks. The implemented manipulator showed that morphology, such as joint angle limit and muscle-tendon arrangement, provides dexterity and structural stability to flexible manipulators. These results are suggestive for biology because they indicate that actual birds may also use the proposed mechanism and control laws.

Study of downlink secrecy rate in Massive MIMO employing 1-bit ADCs/DACs in the presence of pilot attack

In this paper, we present results from a world-first radiant cooling pavilion, demonstrating a method of cooling people without cooling the air. Instead, surfaces are chilled and thermal radiation is used to keep people cool. A thermally-transparent membrane is used to prevent unwanted air cooling and condensation, a required precursor to deploying radiant cooling panels without humidity control in tropical environments. The results from this thermal comfort study demonstrate the ability to keep people comfortable with radiation in warm air, a paradigm shifting approach to thermal comfort that may help curb global cooling demand projections.