Miracle-dz/UniFAR-FTUs huggingface dataset:
Predictive Traffic Engineering Incorporatingreal-World Information Inspired by the Cognitiveprocess of the Human Brain

The amount of traffic on the Internet has been increasing both in quantity and in fluctuation as the devices connected to the Internet and the services on the Internet become popular. Predictive Traffic Engineering (TE) is one approach to accommodating fluctuating traffic without causing congestion. Prediction accuracy is important for predictive TE. Real-world information is useful for the prediction of future traffic. Although the real-world information may contribute to the accurate prediction of future traffic, it is difficult to model the relation between these two types of data. Therefore, we propose a prediction method inspired by the cognitive process of the human brain, which makes decisions from uncertain information. Our method defines multiple states based on the monitored information including both traffic and real-world information and subsequently learns the future traffic corresponding to each state. Then, our method predicts future traffic by deciding the current state from the traffic and real-world information by using a process inspired by the cognitive process of the human brain. Finally, our method allocates resources based on the future traffic corresponding to the states of which the confidence levels are high. We evaluated our method by simulation. The results demonstrate that our method avoids congestion without requiring a large amount of additional resources; the amount of resources required to avoid congestion is reduced by 25 % compared with the predictive TE using only past traffic information.
Neglect or unknown nail under the carotid sheath - accidental discovery

Presence of a foreign body in the vascular space of the neck is a very rare pathology. Long lasting metallic objects in this area induce significant changes in a vital zone, whose damage can cause high morbidity. This metallic foreign body a nail was purely accidental discovered at a neurological consultation in a patient working as a carpenter. The metallic foreign body was removed from the cervical region without complications. Anamnesis identified a traumatic event, with no complications encountered, that took place 20 years ago.
A new IDS for detecting jamming attacks in WBAN

Thanks to the Internet of Things (IoT), our life becomes more flexible in various areas, like emergency, transport, building management and healthcare. Our work focus on the health technology named Wireless Body Area Network (WBAN), which consists of mini medical sensors. Those sensors are attached on the human body to collect biomedical parameters and send them to the medical center. However, because of the presence of wireless network the use of those applications are very sensitive to various types of exterior attacks and anomalies, which make the field of security a very big challenge. Jamming attacks are one of the most dangers attacks in WBAN system, which disrupt and block the communication between the medical sensors. This paper proposed a novel Intrusion Detection System (IDS) based on the network parameters, which is able to differentiate the normal state and abnormal state as false alerts from jamming state. Our proposed technique also allows us to identify three types of jamming in order to decrease the false alarms rates and increase the detection rates. Finally, this IDS mechanism is simulated in Castalia platform, which is based on the OMNET ++ simulator.
Arabic Text Classification in the Legal Domain

The field of law in Morocco is behind on progress to other fields, where the archiving of legal documents is done manually and the access to the information is increasingly complex. In the scope of this work, we investigate the application of text classification methods to support law professionals, by proposing a system able to automatically select the class of a judgement. We will build four models which are Naïve Bayes, K-Nearest Neighbor, Support Vector Machine and Decision Tree to classify Arabic legal documents, which are tried by the Moroccan court.
Investigating Connection Algorithms Among Drones in The DRANET System

DRANET is Ad hoc Drone Network, where a Drone system is connected to a Drone peer, the system communicates a consistent manner in collaborative work. The DRANET systems are Drone systems work in equilibrium and with communication sharing. The DRANET system problem is the operational flight balance and service system to the user. The algorithm design of DRANET consists of twenty-two logical functions of the system. The paper is the results of the Drone logic flight investigations in the herd. Algorithms provide rules about how DRANET in a system does not collide with each other in forming flight formations, flies equilibrium. DRANET systems are designed to serve communication when people gather for public meetings or support communication links in order to restore an emergency.
Accelerated PSO-Scaled PI Controller for DC-DC Boost Converter in Photovoltaic Systems

In the following paper, the parameters of the Proportional-Integral (PI) controller of the DC-DC boost converter are tuned with and without using the accelerated particle swarm optimization algorithm (APSO) and the performance of the converter is analyzed under the effect of the variable irradiation level of the photovoltaic (PV) module. The mathematical modeling of the photovoltaic module is implemented in the MATLAB/Simulink having two variable parameters, temperature and irradiation level to change the output of the module. The output of the PV module is fed to DC-DC boost converter having a particular value of the duty cycle ratio to increase the voltage to the desired constant value. A three phase sinusoidal pulse width modulation (SPWM) inverter having DC link voltage coming from the converter’s output is simulated in the MATLAB/Simulink and a three phase resistive load is connected across the output terminals of the inverter to get phase and line voltages of the inverter. The irradiation level is used as a variable parameter having a step change at regular intervals and the output voltage of the DC converter under the close feedback system is observed. A comparison is made between the tuning parameters of the PI controller calculated with and without using the Accelerated particle swarm optimization algorithm.
Enhanced Sensitivity of Temperature Sensor with Transmitted Light of Fiber Bragg Grating

An optical temperature sensor utilizing transmitted light of fiber Bragg grating (FBG) is experimentally demonstrated in this work. For performance comparison, sensitivity of FBG transmitted light is compared with that of FBG reflected light. The measured sensitivity of transmitted light is 15.3 pm/°C, which is higher than 14.8 pm/°C recorded for the reflected light. Such enhanced sensitivity is influenced by the 3-dB bandwidth of the light signal. It is demonstrated that the transmitted light has narrower bandwidth of 0.12 nm rather than 0.23 nm for the reflected light and this factor contributes to enhanced sensitivity for the transmitted light.
A Smart Sensor Node with Smartphone based IoMT

Long-term and continuous monitoring of physiological parameters like Blood Pressure (BP), Heart-Beat Rate (HBR), and Electro-cardiogram (ECG) are of very important in ensuring proper medical care. Presently, all these measurements involve separate medical equipment. Most of the portable or wearable solutions require high-power, and are often too heavy to wear. In this paper, the design of a wearable wireless sensor node has been proposed that can collect all the required data and send them to the smartphone. The smartphone is used to perform the desired processing tasks like digital filtering, normalization, feature extraction, etc. In the proposed design, the smartphone further acts as an IoMT (Internet of Medical Things) gateway to send all processed data to the IoT cloud for medical use. This will eventually reduce the amount of power consumption at the sensor-node.
¿Son clínicamente significativas las células escamosas atípicas que no pueden excluir lesiones escamosas intraepiteliales de alto grado?

Objetivo. Determinar el riesgo acumulado de neoplasia cervical intraepitelial CIN 2‐3 en pacientes con células escamosas atípicas que no pueden excluir HSIL (ASC‐H). Métodos. Se llevó a cabo un análisis retrospectivo para identificar pacientes remitidas a la clínica de displasia con ASC‐H. En la evaluación inicial se sometió a todas las pacientes a colposcopia, realizando curetaje endocervical y biopsia ectocervical cuando estaban indicadas. Se efectuó una evaluación de seguimiento a los seis y doce meses. El criterio clínico de valoración fue el diagnóstico histológico acumulado de CIN 2‐3 a los doce meses. Resultados. Se evaluó un total de 229 pacientes con ASC‐H y una edad media de 32,8 años. En el momento de la colposcopia inicial, sólo el 10,0% de las pacientes (23/229; IC 95% = 6,5%‐15%) presentaba signos histológicos de CIN 2‐3. El riesgo acumulado de sufrir CIN 2‐3 fue del 12,2% (IC 95% = 8%‐17%). Conclusiones. La evaluación de pacientes con ASC‐H mediante colposcopia permite la detección de CIN 2‐3, pero quizá en un porcentaje inferior al publicado anteriormente en otros estudios. ▪
Study to Analyze the Impact of Fixed Trap Charges on the Performance of Germanium Ferroelectric Double Gate FET (GeFeDGFET)

This paper presents the study on the influence of fixed trap charges on device characteristics of Germanium Ferroelectric Double Gate FET (GeFeDGFET). The fixed trap charges have been incorporated with the 2D Poisson’s equation and concurrently solved with Landau-Khalatnikov equation to obtain the device parameters of GeFeDGFET. The analysis of results has shown that the presence of negative trap charges degrades device performance and positive traps enhance device performance. However, the characteristics of GeFeDGFET even with the negative traps have found to be much superior to those for conventional GeDGFET (Germanium Double Gate FET). The incorporation of ferroelectric layer has resulted in an enormous enhancement in potential barrier, threshold voltage, gain, capacitance, ON-state current, transconductance etc as compared to conventional device.
IoMT Malware Detection Approaches: Analysis and Research Challenges

The advancement in Information and Communications Technology (ICT) has changed the entire paradigm of computing. Because of such advancement, we have new types of computing and communication environments, for example, Internet of Things (IoT) that is a collection of smart IoT devices. The Internet of Medical Things (IoMT) is a specific type of IoT communication environment which deals with communication through the smart healthcare (medical) devices. Though IoT communication environment facilitates and supports our day-to-day activities, but at the same time it has also certain drawbacks as it suffers from several security and privacy issues, such as replay, man-in-the-middle, impersonation, privileged-insider, remote hijacking, password guessing and denial of service (DoS) attacks, and malware attacks. Among these attacks, the attacks which are performed through the malware botnet (i.e., Mirai) are the malignant attacks. The existence of malware botnets leads to attacks on confidentiality, integrity, authenticity and availability of the data and other resources of the system. In presence of such attacks, the sensitive data of IoT communication may be disclosed, altered or even may not be available to the authorized users. Therefore, it becomes essential to protect the IoT/IoMT environment from malware attacks. In this review paper, we first perform the study of various types of malware attacks, and their symptoms. We also discuss some architectures of IoT environment along with their applications. Next, a taxonomy of security protocols in IoT environment is provided. Moreover, we conduct a comparative study on various existing schemes for malware detection and prevention in IoT environment. Finally, some future research challenges and directions of malware detection in IoT/IoMT environment are highlighted.
Karna: A Gate-Sizing based Security Aware EDA Flow for Improved Power Side-Channel Attack Protection

Power side-channel attacks pose a serious threat to the security of embedded devices. Most available countermeasures have significant overheads resulting in the application not meeting its requirements of low-power, high-performance and small area. We propose an algorithm called Karna11Karna, much like Achilles from Greek mythology, was born with a shield that protected him from attacks. Similarly, Our proposed scheme, Karna protects the design from power side-channel attacks in the manufacturing phase or in other words the chip is manufactured(born) with a shield. that can be incorporated in the Electronic Design Automation (EDA) flow, in order to significantly improve the side-channel security of the device, without impacting the other device characteristics. Karna does not add additional logic but rather achieves this by first identifying vulnerable gates in the design and then reconfiguring these gates to increase side-channel resistance. Unlike contemporary works, Karna does not require any specialized gate library but uses the gates available in the standard cell library. We integrate Karna into the Synopsys Design Compiler and demonstrate its efficacy at reducing side-channel leakage in implementations of AES, PRESENT and Simon block ciphers, synthesized for a 28nm technology node. An interesting observation is that Karna only uses the available space around the gates to perform this optimization and does not incur any additional area overheads. We showcase the side-channel resistance of these optimized designs using a Differential Power Analysis attack. Our proposed approach is able to reduce the power side-channel of the designs while incurring no penalty in delay, power and gate-count.
Dr. CU 2.0: A Scalable Detailed Routing Framework with Correct-by-Construction Design Rule Satisfaction

Detailed routing becomes a crucial challenge in VLSI design with shrinking feature size and increasing design complexity. More complicated design rules were added to guarantee manufacturability, which made detailed routing an even harder task to achieve in the design flow. In this paper, we propose a detailed router that judiciously handles hard-to-access pins and new design rules including length-dependent parallel run length spacing, end-of-line spacing with parallel edges, and corner-to-corner spacing. Our experimental results show that our framework can effectively reduce the number of violations with comparable wirelength. Comparing our algorithm with the best score of each released designs in the ISPD'19 Contest, there is 2% score improvement. Compared with the state-of-the-art work [1], our algorithm achieves 69% better scores. The source code of Dr. CU 2.0 is available at https://github.com/cuhk-eda/dr-cu.
A Review of Recent Advances in Image Co-Segmentation Techniques

Recent advances in the corporate processing of images have exhibited its advantages over the individual processing. Image co-segmentation aims to segment shared objects from two or more relevant images, and is becoming more and more interesting for computer vision researchers. Many applications need accurate and efficient segmentation techniques: indoor navigation, autonomous driving, and virtual reality systems to name a few. Although numerous techniques have been proposed, it is still lacking a deep review of image co-segmentation techniques. In this paper, we provide a review on the fundamentals and challenges of image co-segmentation techniques. We organize the recent advances of image co-segmentation into seven major frameworks: graph based framework, clustering based framework, partial differential equation based framework, quadratic programming based framework, low rank matrix recovery based framework, joint optimization based framework, and machine learning based framework. We expect this review to be beneficial to both fresh and senior researchers in this field.
Design and FPGA Implementation of a Pseudorandom Number Generator Based on a Four-Wing Memristive Hyperchaotic System and Bernoulli Map

Random numbers are widely used in the fields of computer, digital signature, secure communication and information security. Especially in recent years, with the large-scale application of smart card and the demand of information security, the demand for high-quality random number generator is increasingly urgent. With the development of the theory of non-linear systems, the design of pseudorandom number generator (PRNG) for chaotic behavior of non-linear systems provides a new theoretical basis and implementation method. This paper presents a PRNG based on a no-equilibrium four-wing memristive hyperchaotic system (FWMHS) and its implementation on Field Programmable Gate Array (FPGA) board. In order to increase the output throughput and the statistical quality of the generated bit sequences, we propose the PRNG design which uses a dual entropy sources architecture with FWMHS and Bernoulli map. Simulation and experimental results verifying the feasibility of the FWMHS are also given. Then, the proposed PRNG system is modeled and simulated on the Vivado 2018.3 platform, and implemented on the Xilinx ZYNQ-XC7Z020 FPGA evaluation board. The maximum operating frequency has been achieved as 135.04 MHz with a speed of 62.5 Mbit/s. Finally, we have experimentally verified that the binary data obtained by this dual entropy sources architecture pass the tests of NIST 800.22, ENT and AIS.31 statistical test suites with XOR function post-processing for a high throughput speed. The security analysis is carried out by means of dynamical degradation, key space, key sensitivity, correlation and information entropy. Statistical tests and security analysis show that it has good pseudorandom characteristics and can be used in chaos-based cryptographic applications at hardware or software implementation.
A Time Frequency Tensor Framework for DOA Estimation: Application to MIMO Systems

In this paper, we show that the DOA estimation problem can be solved through a tensor representation of the non-unitary joint diagonalization of spatial quadratic timefrequency. We use an approach to select time-frequency points to construct the set of matrices forming a third-order tensor. Then, the determination of DOAs is solved by Parallel Factor analysis. The main advantage of this method is that it does not require any whitening stage, and thus, it is intended to work even with a class of correlated signals. Numerical simulations are provided in order to illustrate the effectiveness and behavior of the proposed approach.
A new collaborative approach to solve the gray-sheep users problem in recommender systems

Recommender systems aim to help users to find items that fit their requirements and preferences. In that field, the collaborative filtering (CF) approach is considered as a widely used one. There are two main approaches for CF: memory-based and model-based. Both of the two approaches are based on the use of users' ratings to predict the top-N recommendation for the active user. Despite its simplicity and efficiency, The CF approach stills suffer from many drawbacks including sparsity, gray sheep and scalability. The aim of this work is to deal with the gray sheep problem, by proposing a novel collaborative filtering approach. This novel approach aims to enhance the accuracy of prediction by turning the users whose preferences disagree with the target user, into new similar neighbors. For instance, if a user X is dissimilar to a user Y then the user $\lnot$X is similar to the user Y.To evaluate the performance of the proposed approach, we have used two datasets including MovieLens and FilmTrust. The Experimental results show that our approach outperforms many traditional recommendation techniques.
Design of an IMU-independent Posture Recognition Processing Unit for Head Mounted Devices

We propose a design of a posture recognition processing unit (PRPU) for head mounted devices (HMDs) independent of inertial measurement unit (IMU) types. We design whole system for the PRPU including the control driver and the communication packets. Since any IMU can be attached to the designed processing unit, the hardware developer can select an IMU for their device according to user applications. The proposed design is also can be applied as a co-processor of another processor to reduce the computational burden.
YOLO based Intelligent Tracking System for Curling Sport

In view of the current situation of the tracking system, which requires human control and is not intelligent enough, this paper designs an intelligent tracking system. The system uses the deep learning method to detect the objects, completes the analysis of the content of the image, and realizes intelligent tracking. Taking the curling movement as an example, the application of the intelligent tracking system is realized. In the experiment, the accuracy rate of the YOLO v2 model curling automatic shooting system detection data set was 94.3%, and the detection speed reached 30 f/s. The YOLO model can meet the real-time requirements of the curling and shooting system. In the actual process of shooting, the system was completed the tracking task.
Influence of Powder-Liquid Ratio on Self-Setting Apatite Cement in Bone Repair.

本研究は自己硬化型アパタイトセメント (HAP-C) の粉液比の違いにより, 骨修復能にどのような影響があるかを検討した。 実験には健常雑種成犬9頭を用いた。 下顎左右第1前臼歯から第4前臼歯の抜歯3ヵ月後に, ステントを用いて骨窩洞 (φ3.2mm×3.0mm) を作製した。 1) 粉液比0. 4と0. 6のHAP-C, 2) ポロシティー0%と70%のHAP-Cをそれぞれの骨窩洞に充填した。 術後2週から8週で屠殺し, 組織切片を作製し組織学的観察を行った。 実験期間を通じてすべてのHAP-C群の硬化体周囲組織には目立った異物反応がほとんど観察されなかった。 形成された新生骨は, すべてのHAP-C硬化体に直接接していた。 粉液比0. 4とポロシティー0%のHAP-Cは骨窩洞内に硬化体が残留し, 粉液比0. 6とポロシティー70%のHAP-Cは硬化体内部が新生骨に置換していた。 これらの結果から, 多孔質構造に変化を生じ, 生体内のHAP-C硬化体で骨置換を生じたことが示唆された。
A Low Complexity and Cost Method to Diagnose Arterial Stenosis Using Lightwave Wearables

In this paper, we present a novel low cost and low complexity platform for the provisional diagnosis of vessels abnormalities, such as artery stenosis, aneurysms, etc. The proposed system is based on a low cost lightwave wearable device and advanced machine learning techniques to reduce the computational load and improve the accuracy of diagnosis. Specifically, in this work we focus on the image reconstruction in the case of an artery stenosis due to atheromatic plaque, where we briefly present the method and some preliminary results. The proposed platform can automatically provide a provisional diagnosis which can then be followed-up with further detailed and/or established imaging methods (e.g., Doppler ultrasound, Magnetic Resonance Angiography, etc) and treated promptly in order to minimize their likelihood of progression to higher levels of severity. This method may act as an adjunct to existing established screening programmes (e.g., arterial stenosis and aneurysm screening) or be used for new forms of population screening in the future.
Vitamin D in der onkologischen Intervention: Update 2015

Zusammenfassung Bei Krebspatienten findet sich Vitamin-D-Mangel häufig und ist mit der Prognose und der Krankheitsprogression assoziiert. Bei Brustkrebspatientinnen konnte unter einer Anthrazyklin- und Taxan-haltigen Polychemotherapie ein deutlicher Abfall des 25-OH-D-Spiegels beobachtet werden. Der 25(OH)D-Status sollte bei allen Krebspatienten bei Tumordiagnose kontrolliert und durch adäquate Supplementierung kompensiert werden. Dies gilt insbesondere für Krebspatienten mit schlechtem Ernährungsstatus, Therapien mit Anthrazyklin-, Taxan- und monoklonaler Antikörper-haltiger CTX sowie bei muskulären, mukokutanen Störungen, Fatigue und Tumorkachexie.