Miracle-dz/UniFAR-FTUs huggingface dataset:
A Systematic Review: Detection of Anomalies in Social Networks

As the Internet is growing drastically, interest in online social networks has also dramatically increased over the past ten years. They are among the most widely used websites on the Internet, with applications in practically every aspect of life, including telemarketing, entertainment, healthcare, and business. However, as they are being used broadly, they have become the main targets for malevolent individuals who try to engage in a wide range of fraudulent or unlawful activities and harm other users. Therefore, it is vital to detect unusual activity, especially in social networks, as this enables the identification of crucial data pertaining to the behavior of unusual individuals (Anomaly detection). It is challenging to identify unusual and unpredicted user behavior by diving into the network’s hidden patterns, as these users’ engagement patterns differ greatly from those of other users. Although numerous techniques have been created for identifying anomalies in various problematic environments, this discipline is quite new and expanding quickly. As a result, this growing field of anomaly identification in social networks requires systematic analysis. By following the systematic literature review practice, the most relevant research papers from the data resources are selected by using search string keywords, de fi ne d inclusion/exclusion criteria, and the proper analysis of the selected research papers. The data collected is used to answer research questions. An exhaustive analysis of different techniques and approaches is performed by assessing them on the research methodology. This entire activity took around three to four months for a thorough analysis of relevant research papers. Upcoming researchers may work on the research gaps by checking on the proposals mentioned in this review paper.
CLCA: Contrastive Learning Using Combined Additional Information for Alzheimer's Diagnosis

Alzheimer's disease (AD) is a cognitive disorder that often occurs in the elderly. In the early stage of the disease, memory loss is the primary manifestation, which is clinically called mild cognitive impairment (MCI). At present, there is no way to prevent or reverse AD. Therefore, it is essential to diagnose the disease in time. There are many studies using computers to diagnose AD automatically. Because the cause of the disease is unclear, using deep learning to diagnose AD from MRI data is a hot research topic today. In addition, for the 3-D medical imaging field, it is challenging to build a large dataset for a particular disease. Contrastive learning demonstrates strong capabilities and provides a way to learn knowledge from the images themselves. However, in this process, the additional information of participants is not used, and many studies have found that factors such as sex and age significantly influence the disease. So we improved the existing training method to take the age and sex of the participants into account and improve the encoding ability of the neural network. We validate performance on the ADNI dataset; our method outperforms training from scratch and state-of-the-art methods on AD diagnosis tasks after fine-tuning.
EUV lighting by the cold cathode C-beam irradiation technique

EUV lithography has been introduced for high-volume manufacturing in the semiconductor industry. The recent development of EUV lightings with a wavelength of 13.5 nm has extended semiconductor technology to a node region of several nanometers. The EUV is generated by the C-beam irradiation, which is controlled by the C-beam structure, incident angle of the electron, anode voltage, and anode current.
Wideband Dual-Polarized Magneto-Electric Dipole With High Isolation

A wideband magneto-electric (ME) dipole antenna with high-isolation is proposed by using different polarization modes. The proposed ME-dipole antenna consists of four dipoles and two orthogonal feeding networks. High isolation is achieved by adopting different polarization methods and increasing the distance between feeding networks. At the same time, by adjusting the various parameters of the antenna feed structure, a wideband magneto-electric dipole antenna with stable radiation performance can be obtained. According to the final simulation data results, the proposed antenna has an impedance bandwidth of 31.5% from 2.83 to 3.89 GHz for the reflection coefficient of less than -10 dB, and the isolation of the proposed antenna is higher than 42 dB.
Miniaturized Phase Shifter Based on D-CRLH Resonator Using Phase Alignment Element

In this paper, a filter phase shifter based on D-CRLH resonator is proposed, which can not only provide constant phase shifting and filtering functions, but also has a compact structure and wide stopband rejection characteristics. Firstly, this paper adopts the D-CRLH structure as a single resonator to design the filter. This structure has a compact structure and multiple structural parameter variables, which makes this design have a high degree of freedom. Secondly, the resonance characteristics of the D-CRLH structure are analyzed by the equivalent circuit method, and the mapping relationship between the characteristics of the resonator and the equivalent circuit is established, which effectively shortens the design cycle. Finally, two band-pass filter branches are adopted to design the filter phase shifter, and the phase adjustment is carried out through the phase alignment element. Therefore, the designed phase shifter has better phase shift flatness while having the functions of phase shifting and filtering. The experimental results show that the center frequency of the phase shifter designed in this paper is 2.4 GHz, which can provide a phase shift value of 90° ± 2.6° in the frequency band of 2.13-2.6 GHz (fractional bandwidth is 19.58%).
A Ka-band BCB based Back-to-Back BGA Transition for 3D Heterogeneous Integration

This paper presents a Ka-band back-to-back BGA transition for the 3D heterogeneous integration based on BCB. Impedance matching structures are designed to compensate for the discontinuities caused by BGA. The transition is fabricated by the silicon-based MEMS photosensitive composite-film process. The simulated and measured results show that the transition has a 15 dB impedance bandwidth from 26 GHz to 40 GHz, and its insert loss values better than 1.5 dB up to 36 GHz per pass through one BGA transition.
A Ku-Band 40W GaN Power Amplifier MMIC for Satellite Communication

A Ku-band high power amplifier (HPA) MMIC is designed based on 0.15 μm GaN HEMT process. To improve the HPA efficiency, a compact and concise 16-way power synthesis network is applied to reduce the insertion loss of match networks. Meanwhile, the optimal third-order intermodulation distortion (IMD3) impedance is taken into account to improve the linearity. The measured results under continuous wave (CW) excitation show that the power-added efficiency (PAE) is more than 36% with output power over 46dBm (40W) among 13-15.5 GHz, while the IMD3 is better than -24 dBc at 40dBm output power (two tones) back-off (PBO). The total chip size is 3.7×5.9mm2.
Ka-band 20W power amplifier MMIC for satellite communication

Based on AlGaN/GaN HEMT, a Ka-band 20W power amplifier(PA) monolithic microwave integrated circuit (MMIC) was developed. The three-stage cascaded amplifier structure was adopted. In the final stage, the lange power distribution and synthesis matching network was used to realize 16-cell power synthesis. The low-pass reactance matching network was used at the input and inter stage of the circuit, and the band-pass reactance matching network was used at the output stage. Which was combined with the stable network to ensures the gain, power and efficiency characteristics.The measurement results show that in the frequency range of 27-31GHz, the power gain is greater than 22dB, the power additional efficiency is greater than 25%, and the saturated output power is up to 20W in continuous wave. The high power amplifier is suitable for satellite communication ground station systems.
A 110-163GHz T/R Switch Using Coupled Lines and Negative Biasing in 40nm CMOS

The paper presents a 110-163 GHz integrated transmit/receive (T/R) switch in 40nm CMOS. The proposed T/R switch is based on a switchable resonator with coupled lines. The coupled lines work as balun and also matching network. In addition, negative gate/body-biasing is introduced to reduce the parasitic capacitance of parallel switch transistors in the off state, and therefore to improve the insertion loss and power handling capability. The fabricated T/R switch features a measured insertion loss of 3.5 dB, an isolation of 38 dB, and a simulated P1dB of 13.3dBm at 140 GHz. The switch has no power consumption. The core chip area is only 0.0088 mm2. The proposed switch presents good overall performance among the compared CMOS switches at similar frequencies.
Design of Rectifying Metasurfaces for Wireless Energy Transmission Systems

a novel rectifying metasurface (MS) with low power consumption and high efficiency is applied to wireless energy harvesting. The proposed metasurface structure consists of an array of cells with diodes, a dc feed, and a load. A new approach which adds rectifier diodes to MS cells is proposed. This practice eliminates the impedance matching circuit connected between metasurface absorber and rectifier diode, which can simplify the structure. Some simulation results are given, these results show that rectification efficiency can reach over 60% at 5.2GHz.
A 1-Bit Wideband Circularly Polarized Reflective Reconfigurable Metasurface with Sequentially Rotated Elements in Ku-band

This paper proposes a 1-bit wideband circularly polarized reflective reconfigurable metasurface (CPRRM) in Ku band. The 1-bit CPRRM element consists of a asymmetric U-slot patch and a 1-bit reflection-type phase shifter (RTPS) controlled by only one PIN diode which can tune the element states, '0' or '1', as it flipped. To improve the axial ratio (AR) bandwidth, the sequential rotation technique (SRT) is applied to the full array configuration. A 24 × 24 (10.2 λ0 × 10.2 λ0, where λ0 is the wavelength at 15.0 GHz) CPRRM is built and analyzed using a commercial full-wave simulator. The simulated broadside gain is 23.5 dBi at 15 GHz with 3-dB bandwidth of 13.75 % in left-handed circular polarized (LHCP). The relative bandwidth of 3-dB AR is 12.61%.
A Review of Multidata Human Activity Recognition

Human Activity Recognition (HAR) has become one of the most known and prominent research area in a variety of sectors during the last few decades. As a result, HAR can be used to keep tabs on a wide range of activities and the environment in general, all according to the user’s choices. HAR aims to categorize human actions in order to better understand how people behave. Its adaptability has recently piqued the curiosity of computer vision experts. RGB, skeleton, depth, infrared, point cloud, event stream, auditory, acceleration, radar, sensors, and Wi-Fi signals are just a few of the data techniques that can be used to describe human actions; each storing a slightly different collection of potentially relevant but separate information and each with their own set of benefits depending on the context of use. As a result, numerous previous articles attempted to investigate HAR methods through various means. The proposed method classifies the intelligence methods to HAR according to the various modalities from which input data can be collected and provide an in-depth examination of their relative merits and shortcomings. In this study, a comprehensive overview of current state of art in artificial intelligence is provided by including device modalities, data modalities, obstacles, and applications in HAR feature direction. The study provides some thoughts and proposals for future research based on the comparison of many HAR benchmark datasets.
An Improved Millimeter Wave MOSFET Model Based on BSIM4

This paper presents a MOSFET model based on BSIM4 model. The improved model takes the coupling between the interconnection lines of the RF multi-finger MOSFET and the ground, substrate coupling effect into account to characterize the parasitic effects of transistors at high frequency. To verify the model, a millimeter wave MOSFET with 8 fingers in 65-nm CMOS LP process is fabricated and measured. The Y-parameters and S-parameters of the model are verified with measurement data from 0.1 to 50 GHz. The minimum value of normalized root-mean-square error (NRMSE) is 1.85% for Y-parameters in the whole investigating frequency range. Compared with conventional BSIM4 model that does not consider the interconnection coupling effect, the model in this work shows better accuracy.
Adaptive Taylor-Sail Fish Optimization based deep Learning for Detection of Black Hole and Sybil Attack in Wireless Sensor Network

Wireless Sensor Network (WSN) is the network of minimal expensive and tiny devices for sensing, which is known as sensors. These networks are vulnerable to various types of attacks namely black hole attack, Sybil attack and so forth. Black hole attack is the most harmful attack and also the access way for all the other types of attacks, whereas Sybil attack is a dangerous hazard to sensor networks in which sensor nodes have numerous identities. These attacks may interrupt the performance and functioning of network, which may cause harm to the network system if not properly detected. Hence, an efficacious technique is proposed for black hole and Sybil attack detection utilizing Adaptive Taylor Sail fish optimizer (Adaptive Taylor-SFO) algorithm. Firstly, WSN nodes are simulated in a network and thereafter, routing is executed by Adaptive Taylor-SFO, which is newly designed by an integration of Adaptive concept with Taylor series and Sail Fish optimizer (SFO) for selecting an optimal route by consideration of fitness measures namely, delay, energy, and distance. Finally, detection of black hole and Sybil attack is carried out by Deep stacked auto encoder. Moreover, the network classifier is tuned employing proposed Adaptive Taylor-SFO. Thus, the proposed technique effectually classified into normal, black hole and Sybil attack. Additionally, proposed technique obtained minimal delay of 19.91ms, FNR of 0.0773, FPR of 0.1026, maximal throughput of 125.73kbps and maximal PDR of 97.52%.
Theoretical Analysis on Linear Array of Microstrip Magnetic Dipoles with Unequal Lengths

Microstrip magnetic dipole antennas have been used in many antenna designs, however, its radiation pattern function has not been obtained in previous researches. In this work, the radiation pattern function of microstrip magnetic dipole antenna resonating in the fundamental mode are derived. The theoretical results agree with the simulated results. Further, we obtain the radiation function of linear Array of microstrip Magnetic dipoles with unequal lengths. The lengths are optimized for sidelobe suppression. An array synthesis approach is given to optimize the linear Array. The results show that linear array of microstrip magnetic dipoles has a much lower sidelobe than the array of electric dipole with the same total length.
A Mutual Intrusion Detection System for MANET to Address DDoS attacks using Data Mining Techniques

A type of wireless communication network called a mobile ad hoc network (MANET) is composed of numerous flexible components that can move in any of the network’s many directions. The Intrusion Detection System (IDS) is a systematic tool implemented to spot suspicious activity with network malfunctions and sends an alert to the security control center. A malicious effort to interfere with the server’s or networks regular operation is acknowledged as a distributed denial-of-service (DDoS). This occurrence causes the networking system’s general performance to decline. Certain measures must be put into place to improve efficiency. These DDoS attacks are classified as application layer attacks, protocol attacks, and volumetric attacks in the networking system. The server experiences downtime as a result, and the network’s general performance suffers. When resources are brought back into the network, it causes external tension. Data mining methods can be used to find this and fix it.
High-performance Thin-barrier InGaN Channel DH-HEMT for Millimeter Wave Applications

In this work, we reported the thin barrier InGaN channel double-heterostructure high electron mobility transistor (DH-HEMT) for millimeter wave power amplifier (PA) application for the first time. The fabricated device achieved high DC and RF characteristics, including the off-state leakage current as low as 2.6×10-8 A/mm, the large ION/IOFF current ratio of 108, and the on-resistance of 2.7 Ω•mm. The saturation current collapse ratio (CCR) of the device is only 5.8% under the double pulse test. The peak current-off frequency (fT) and maximum oscillation frequency (fmax) of the device are 50 and 131 GHz, respectively. At the large-signal power response in the millimeter wave band, the saturation output power density of the device is 1.5 W/mm, and the linear gain reaches 10 dB. This work shows great potential for the thin barrier InGaN channel DH-HEMT applied for high-performance millimeter wave PA applications.
A Compact HF-UHF Dual-Band Wearable RFID Tag for Body Temperature Monitoring

In this paper, a wearable semi-active RFID tag for body temperature monitoring is designed based on the equivalent model of the human body, which can work in high-frequency (HF) and ultrahigh-frequency (UHF) bands. A small loop structure is used as the matching part to realize the conjugate matching between the input impedance of the UHF tag antenna and the impedance of the tag chip. The bent UHF antenna is designed inside the HF antenna to achieve a compact dual-band antenna design. One part of the antenna's radiation arms is designed to be the same shape and size as the battery to reduce the interference caused by metallic battery on the UHF antenna, then the battery can be stacked on top of one part. Simulated results show that the -10 dB impedance bandwidth of the UHF antenna covers the global UHF RFID band (840-960 MHz), and the resonance of around 13.56 MHz also can be achieved when a matching capacitor is connected in parallel to the input port of HF antenna.
Effective Funneling Length in Alpha-Particle Induced Soft Errors

The funneling phenomenon in alpha-particle induced soft emors is investigated usi-ng a 3-D device simulator(CADDETH), a simple diffusion model(USnneU), and experimental results. Effective funneling length(Ltr) which is different from Huts model is proposed as a guideline for submicron memory cell/devi-ce design. Effective funneling length was found to strongly depend on memory cell size (size effect) and on the proximity of adjacent cells (proximity effect), as well as on substrate impurit.y concentration. A critical collected cha::ge for mega-bit DRAI{ cells can be quantitatively calculated based on these new findings concernj-ng the funneling phenomenon and the proposed sirnulation method.
A CPW-Fed Optically Transparent Broadband Circularly Polarized WLAN Radio Frequency Identification Reader Antenna

In this paper, an optical transparent broadband circularly polarized (CP) radio frequency identification (RFID) reader antenna is presented. The proposed antenna is composed of a soda-lime glass medium and an Indium tin oxide (ITO) layer with 1200nm thickness coated on one side of the medium plate as the conductive layer, with a transparency of more than 80%. The impedance bandwidth and 3dB axial ratio (AR) bandwidth of the antenna are 2.96GHz (1.68-4.64 GHz, 93.67% centered at 3.16 GHz)and 870MHz (2.20-3.07 GHz, 33.01% centered at 2.64 GHz), respectively. The antenna size is 48 × 48 × 1.1 mm3. The radiation efficiency is higher than 50% among the WLAN low frequency band (2.4-2.4835 GHz). Moreover, it has the advantages of optical transparency and wide CP bandwidth, which make it have a wide range of application scenarios.
An Empirical Study of Efficient Malware Detection Analysis on Android Mobile Phones using Machine Learning

Nowadays, smartphones occupy a significant role in everyone’s life; in the present circumstances, android mobile applications as well as their security threats were improved. Therefore, an automatic model is essential to detect malware in smartphones to safe from harmful threats. In recent days researchers were concerned about machine learning-based detection models for detecting the malware which is present in smartphones. Large numbers of ML-based techniques were proposed for android malware detection. Lack of knowledge about the methods available for the detection of malware in the android initiates several challenges. Hence, in this survey, 27 works of literature based on machine learning grounded techniques connected with the malware analysis technique are reviewed. The study of various methods was simplified based on their performance measures as well as the achievement of each method. In addition, the limitations, as well as the improvements of each method, were represented in the study. Eventually, consider the potential future research as well as the challenges in terms of obtaining high accuracy for malware detection. The study methods were reviewed in research gaps and it was represented in the taxonomy diagram.
A Series-Fed Broadband Low Sidelobe Microstrip Array at 24GHz

A 24GHz broadband series-fed microstrip array with low sidelobe performance is designed in this paper. The electric field distribution is changed by loading disturbed branches on one side of the microstrip line, and the electric field on both sides of the microstrip line cannot offset each other. At the same time, the disturbed branches will prolong the current path through the microstrip line, resulting in a lower resonant frequency and improving the impedance matching. The antenna array achieves broadband characteristic while structure is compact. Based on the analysis, a 1 × 8 microstrip linear array is designed. The results show that the impedance bandwidth of the array (|S11| ≤ -10dB) is 13.4%, the average gain in the bandwidth can up to 15.37dBi. The sidelobe level can reach -12.5dB, and it can be further reduced to -19.8dB by Chebyshev distribution.
Survey on IoT based Device for Women Safety

Nowadays, women undergo numerous circumstances that cause them to feel hazardous. Women from different backgrounds face circumstances that cause them to feel undermined in various conditions. It has likewise been demonstrated that in metropolitan places, women are more inclined to encounter badgering particularly in non-industrial nations. For such instances, the device which will illuminate the problems caused (in extreme circumstances) may assist women with feeling more secure, sure and lessen the possibilities of badgering. However there are a couple of Cell phone based application for something similar, it probably won’t be able for a user to open up an application in cell phone in certain circumstances without the information on the culprit. A device based on IOT will be built in this article that utilizes Ultrasonic sensor to convey and to send alarms to them. The GPS are utilized to share the user’s area straight forwardly to the authority and saved contacts. The switch in the device work for sending manual alarms in the event of crisis, then the Buzzer will likewise initiate. In this approach, a device is developed to provide safety to women in their tough situations.