Miracle-dz/UniFAR-FTUs huggingface dataset:
System-Level Counterfeit Detection Using On-Chip Ring Oscillator Array

Counterfeiting has unfortunately become a worldwide epidemic affecting electronic systems from consumer goods to military equipment, which seriously jeopardizes system security, reliability, and electronic vendors’ reputation. The counterfeit parts, e.g., integrated circuits (ICs) and printed circuit boards (PCBs), have shown a significant increase in type and number over the recent years. However, the existing counterfeit detection techniques deal with IC or PCB separately, and hence, they cannot verify the authenticity of an electronic system as a whole. In this paper, we propose concurrent IC and PCB authentication (CIPA), a novel methodology that concurrently verifies the authenticity of both IC and PCB through extracting the signature pairs generated by a ring oscillator (RO) array without/with PCB cavity resonance. With CIPA, remote authentication is allowable by transmitting the signatures between the verifier and the system vendor. The CIPA structure has shown insignificant area overhead (0.945% on average) when implemented on a number of benchmarks. Both CIPA and the benchmarks have been implemented on the authentic and counterfeit FPGA systems, and the results give 100% confidence in detecting counterfeit ones. Furthermore, the authenticity of PCB and IC (i.e., authentic or counterfeit) of the system under test can also be mined from CIPA signatures. According to the experimental results, systems composed of different authenticity states of PCB and IC are differentiated from each other with the confidence of 97.62%. The overall authentication time is $40.2~\mu \text{s}$ considering 50-MHz system clock.
Asymptotically Linear Analysis and Gate Probability Allocation Schemes in Probabilistic Circuits

As the feature size of CMOS technology rapidly shrinks into the very deep submicrometer, the power density is getting higher and the circuit’s reliability is seriously impacted by thermal noise. In order to reduce power dissipation, decreasing the supply voltage is a promising way. However, soft errors and decreased supply voltage make circuits behave probabilistic. Fortunately, some applications can tolerate a certain level of operation errors. The tradeoff between energy and reliability provides an opportunity to save the power consumption in the circuit. An asymptotically linear analysis (ALA) strategy is proposed to model the reliability evaluation of combinational logic circuits. Under the assumption that the gate error probability is not more than 0.05, an asymptotic linear matrix ${{A}}$ is constructed by using the first-order term of the output error probability. When propagating the gate error probability from the input to the output ports, the ALA strategy only requires one multiplication between the matrix ${{A}}$ and the gate error probability vector. There are significant differences in the complexity of computation of the ALA scheme and the Bayesian network (BN) and the probability transfer matrix (PTM) schemes, while its relative error (RE) is no more than 0.08 on the benchmark of LGSynth91. Furthermore, three schemes are proposed to adjust the gate error probability to meet the constraint on the error probability of the probabilistic CMOS (PCMOS) circuit’s outputs. The proposed schemes can be performed to search the gate error probability combinations in the logic and circuit design stage of VLSI. During the power optimization, the switching activity factor in the asymptotically linear region is approximately invariant. It makes the power optimal model convex. The energy-saving ratio of the proposed power optimization scheme is 5%–6% higher than the existing schemes. The time consumption of the proposed three schemes is one-thousandth of the time consumed by the BN and PTM schemes. All the three schemes are verified by conducting experiments on the ISCAS’85 and IWLS’15 benchmark circuits. The simulation results establish the feasibility of the ALA and the performance of the proposed schemes.
FAST DISINTEGRATING DRUG DELIVERY SYSTEMS: AN UPDATED REVIEW

Oral Drug Delivery Route is the most preferred route for the administration of various drugs. Fast-disintegrating tablet (FDT) technology is one of the recent innovative technologies in pharmaceutical formulations and the FDT formulation has become a fast-growing segment in oral drug delivery systems. FDT formulations are the solid unit dosage forms which disintegrate or dissolve rapidly in mouth without chewing and water. FDT formulations are suitable for children, elderly and anyone who has difficulty in swallowing conventional solid dosage forms. This review describes the various formulation aspects, technologies and various drugs which are explored in the field of FDTs.
Research on Pedestrian Recognition Based on DM642 Driver Assistance System on Vehicle

Road pedestrian recognition is a core issue in the field of automotive safety, the pedestrians captured by the video cameras installation on the road ahead of the vehicle. To determine and mark pedestrians and estimate the potential risks according to the image processing and pattern recognition technology. Taking measures to protect pedestrian in the vehicle have important applications in driver assistance. The paper collected road ahead of the vehicle video information in the DM642 hardware platform, extracted the lane edge line by improved Hough transform method, and the extraction of candidate regions according to the features of pedestrians itself, using the Adaboost method of training the classifier. The results show that the classification accuracy rate reached 92%, conform to the real-time performance of the system requirement. With the development of DSP technology, pedestrian’s collection, processing, recognition as one of the embedded pedestrian recognition system has a broad research value and business prospects.
Bacterial quorum sensing applied to the coordination of autonomous robot swarms

This paper proposes a strategy for the coordination of a swarm of robots in an unknown environment. The basic idea is to achieve the autonomous movement of the group from an initial region to a target region avoiding obstacles. We use a behavior model similar to bacterial Quorum Sensing (QS) as a technique for the coordination of robots. This behavior has been described as a key element in the interaction between bacteria, and we use it as a basic tool for local interaction, both between the robot and between the robot and the environment. The movement of the swarm of robots, or multi-agent robotic system, is shown as an emerging behavior resulting from the interaction of agents (in the context of artificial intelligence) from basic rules of behavior. The proposed strategy was successfully evaluated by simulation on a set of robots.
Efficient interest‐aware data dissemination in mobile opportunistic networks

In mobile opportunistic networks, the high mobility of humans and the resource limitation of smart mobile devices pose a great challenge to the design of efficient data dissemination, in which data packets generated from publishers need to be delivered to the subscribers via opportunistic encounters. The current data dissemination schemes generally concentrate on the similarity among nodes while ignoring the similarity between nodes and data packets, which leads to that data packets move back and forth among the nodes with similar social features instead of reaching to the subscribers efficiently. In this paper, an efficient interest‐aware data dissemination approach is proposed in mobile opportunistic networks, in which the similarity between nodes and data packets is used to determine whether a node is a potential destination. Moreover, both the social feature and the residual energy are considered to choose an appropriate relay node, and then determine the number of packet's replicas. The simulation results show that efficient interest‐aware data dissemination provides high efficiency and less transmission overheads compared with the traditional approaches.
Optimizing gait speed and morphology of the foot on a one-legged pneumatic robot

For humans, walking and adapting in various terrains and environments is a natural task. However, strange as it sounds, teaching a robot to take its first steps offers great challenges. Robot adaptation and control is an endless challenge that a substantial amount of researchers strive to solve. The evolutionary robotic research field aims to solve such problems using natural evolution as inspiration. This thesis explores a one-legged pneumatic jumping robot’s ability to automatically adapt to the environment using an evolutionary algorithm. The purpose of this study is to discover whether the robot can automatically adapt to the real world environment by finding optimal gait and morphology. In order to discover whether a robot can adapt to the real world environment, a testing environment and two 3D printed robots were made. The first robot laid the groundwork for the second robot, and was designed to only optimize its gait, in which it successfully achieved using an evolutionary algorithm. The second robot was partly able to achieve its design purposes in terms of optimizing gait and morphology. Several experiments were carried out on the two robots. An early finding was that it is possible to use the evolutionary algorithm to optimize the first robot’s gait. To make the second robot adapt to the natural environment, however, was a more complicated matter as it encountered various challenges leaving the investigation imperfect. On the other hand, the evolutionary algorithm itself performed quite well and the robots was ultimately fit to handle the major stress inflicted by the explosive pneumatic system.
6. Big data security issues with challenges and solutions

: Big data is a collection of huge sets of data with different categories where it could be distinguished as structured and unstructured data. As we are revolutioniz-ing to zeta bytes from Giga/tera/peta/exabytes in this phase of computing, the threats have also increased in parallel. Besides big organizations, cost reduction is the criterion for the use of small- and medium-sized organizations too, thereby increasing the security threat. Checking of the streaming data once is not the solution as security breaches cannot be understood. The data stack up within the clouds is not the only preference as big data technology is available for dispensation of both structured and unstructured data. Nowadays, an enormous quantity of data is provoked by mobile phones (smart-phone) or equally the symphony form. Big data architecture is comprehended among the mobile cloud designed for supreme consumption. The best ever implementation is able to be conked out realistically to make use of a novel data-centric architecture of MapReduce technology, while Hadoop distributed file system also acts with immense liability in using data with divergent arrangement. As time approaches, the level of information and data engendered from different sources enhanced and faster execution is the claim for the same. In this chapter our aim is to find out big data security that is vulnerable and also to find out the best possible solutions for them. We consider that this attempt will dislodge a stride for-ward along the way to an improved evolution in secure propinquity to opportunity.
The effects of 8-year pamidronate treatment on skeletal morbidity in patients with advanced multiple myeloma

Background . In patients with multiple myeloma (MM) osteolytic bone destruction progresses despite a reduction of tumor mass achieved with chemotherapy. The aim of the study was to evaluate the efficacy of pamidronate, an inhibitor of osteoclastic bone resorption administered to MM patients receiving anti-myeloma chemotherapy acc. to the VMCP/VBAP alternating regimen. Material and method . 46 patients with stage III myeloma and osteolytic lesions received either pamidronate (Aredia; Novartis) 60 mg i.v. in 4 – hour infusions monthly (n=23) or chemotherapy alone (control group n=23). Results . On comparison of consecutive skeletal X- ray surveys performed after 6, 12, 18, 24, 30, 36, 42, 48, 54 and 66 cycles of pamidronate the progression of osteolysis was respectively found in 67%, 39%, 27%, 20%, 25%, 25%, 60%, 80%, 92% and 96% of patients. In the control group the corresponding figures were: 79%, 70%, 30%, 44%, 50%, 40%, 66% and 100% (p>0,16). Median time to the occurrence of the first skeletal-related event was 13 months in the pamidronate group and 7 months in the control group. The mean number of skeletal events (pathologic fractures, radiation or surgery of bones and spinal cord compression) per year in the first 4 years of treatment was 1.42 in the pamidronate group and 1.96 in the control group. During further treatment these values reached 0.51 vs 0.9, respectively (p=0.08). At the end of the 8 years the proportion of patients who had developed skeletal events (excluding vertebral fractures) was lower in the pamidronate group as compared to the control group – 52% vs 56%, respectively (p=0.42). The ratio of patients with vertebral pathologic fractures was identical – 76% vs 75%, but the number of vertebral fractures was lower in the pamidronate group than in the control group – 50 vs 71, respectively (1.2 vs 1.77 per year in the first 4 years p=0.07 and 0.84 vs 0.91 in the next 4 years of treatment). During the 4 latter years of study decreases of the blood hemoglobin level occurred with the same frequency among the pamidronate patients and in controls. No significant differences of patient survival were observed between the pamidronate group and the control group (median: 21 vs 20 months from randomization, p= 0.78 and median: 50 vs 45 months since MM diagnosis, p= 0.20). 5-year and 8-year survival was 48% and 30%, respectively, for patients receiving pamidronate, as compared to 17% and 13%, respectively for patients receiving chemotherapy only. Conclusions . Long-term pamidronate treatment moderately reduces myeloma-related skeletal morbidity. As the treatment duration lengthens the effect of pamidronate on skeletal morbidity becomes less pronounced and the difference in the incidence of anaemia between the pamidronate group and the controls is much less distinct. Wp∏yw 8-letniego leczenia pamidronianem powik∏aƒ kostnych w zaawansowanym szpiczaku plazmocytowym C e l. U chorych na szpiczaka plazmocytowego (sz.p.) mimo redukcji masy nowotworowej pod wp∏ywem chemioterapii
Spatial Modulation for Uplink Multi-User mmWave MIMO Systems With Hybrid Structure

Spatial modulation is an efficient transmission scheme for RF-chain limited MIMO systems. In this paper, we design a beam-switching based spatial modulation for mmWave MIMO uplink systems. At user side, a power iteration based algorithm is proposed to generate spatial symbols under the constant modulus constraint. With the generated spatial codebook, the optimal transmission mode is determined. At base station side, a round-robin path selection algorithm is proposed to select paths that are separated in angle of arrival. Inter-user interference is then suppressed by constraining the power of the received spatial symbols over selected paths only. Finally, ordered successive interference cancelation is applied to further reduce interference among users. Numerical results show that the proposed beam-switching based spatial modulation is superior to transmission over the strongest propagation path and is able to yield a satisfactory error performance in mmWave MIMO uplink.
A data mining approach for automated classification of Alzheimer's disease

This work presents the creation of classifiers able to automatically diagnose Alzheimer’s disease from structural magnetic resonance images. Measurements of regions inside the human brain and how they relate to a diagnosis of Alzheimer’s disease are investigated. A genetic algorithm is used to extract a subset of brain measurements which have some of the highest predictive power when compared to the rest of the measurements. A descriptive classifier is created which uses the size of each of the hippocampal volumes of a subject and compares it to the distribution of other subjects. Based on how the individual subject’s measurements compares to the distribution, we can determine whether it is an Alzheimer’s disease predictive volume. This classifier achieves an accuracy equivalent to state-of-the-art approaches. A second descriptive classifier is created using a regression model to predict a healthy subject’s age and applying this to Alzheimer’s disease positive subjects to generate an apparent brain age. The classification accuracy of when the apparent brain age is compared to the subject’s real age is comparable to the state-of-the-art methods in the literature.
Ultrastructural Analysis of Chitosan Antibacterial Activity against Clinical Isolates of Staphylococcus aureus and Escherichia coli

The continuous search for an antimicrobial agent led to the identification of potential antimicrobial biomaterials based on polymers naturals, such as chitosan (CS). However, the mechanism of action of antibacterial activity of CS for gram-positive and gram-negative bacteria was not completely elucidated. The aim of this work is to report the antibacterial activity of CS through ultrastructural analyses of the clinical isolates Staphylococcus aureus and Escherichia coli by Transmission Electron Microscopy. The CS has a bactericidal action against S. aureus and E. coli which alters its cellular ultrastructure, such as with collapsed cell walls, condensed chromatin and the increase of intracellulares structures like vacuoles and cell debris. In this way, the CS represents a potential model for the future design of antibacterial in order to control bacterial resistance of patients in hospital settings.
Stochastic modelling of spatial collective adaptive systems

Collective Adaptive Systems (CAS) are composed of individual agents with internal knowledge and rules which organize themselves into ensembles. These ensembles can often be observed to exhibit behaviour resembling that of a single entity with a clear goal and a consistent internal knowledge, even when the individual agents within the ensemble are not managed by any outside, globally-accessible entity. Because of their lack of a need for centralized control which results in high robustness, CAS are commonly observed in nature – and for similar reasons are often reflected in human engineered systems. Researching the patterns of operation observed in such systems provides meaningful insight into how to design and optimise stable multiagent systems capable of withstanding adverse conditions. Formal modelling provides valuable intellectual tools which can be applied to the problem of analysis of systems by means of modelling and simulation. In this thesis we explore the modelling of CAS in which space (topology and distances) plays a significant role. Working with CARMA (Collective Adaptive Resource-sharing Markovian Agents) a formal feature-rich language for modelling stochastic CAS, we investigate a number of spatial CAS scenarios from the realm of urban planning. When components operate in a spatial context, their behaviour can be affected by where they are located in that space. For example, their location can influence the speed at which they move, and their ability to communicate with other components. Components in CARMA have internal store, and behaviour expressed by Markov processes. They can communicate with each other through sending messages on state transitions in a unicast or broadcast fashion. Simulation with pseudo-random events can be used to obtain values of measures applied to CARMA models, providing a basis for analysis and optimisation. The CARMA models developed in the case studies are data-driven and the results of simulating these models are compared with real-world data. In particular, we explore two scenarios: crowd-routing and city transportation systems. Building on top of CARMA, we also introduce CGP (CARMA Graphical Plugin), a novel graphical software tool for graphically specifying spatial CAS systems with the feature of automatic translation into CARMA models. We also supply CARMA with additional syntax structures for expressing spatial constructs.
Assessment of osteoporosis and fracture risk : axial transmission ultrasound and lifestyle-related risk factors

Osteoporotic hip fractures are associated with high mortality and morbidity rates as well as significant costs. Low-frequency (LF) axial transmission ultrasound is a promising modality for assessing mineral density and geometrical properties. Thus, it may yield additional information on the risk of osteoporotic fractures. This study aimed to evaluate the ability of LF ultrasound to assess osteoporotic status and the risk of fracture in postmenopausal women. Also, lifestylerelated risk factors of hip fractures and the additional discrimination value of combining lifestylerelated risk factors and LF ultrasound velocity were assessed. Two study populations were used. The first consisted of 1,222 older women. Lifestyle-related risk factors and mobility were assessed at baseline. The women were followed for 13 years and the fractures that occurred were recorded. A subgroup of the women was later measured with LF ultrasound and dual-energy x-ray absorptiometry (DXA). The other study population included 95 postmenopausal women whose fracture history was gathered and bone status assessed with LF ultrasound, DXA and peripheral quantitative computed tomography (pQCT). Low body mass and impaired mobility predicted hip fractures. In addition, the risk of cervical hip fracture was increased by low physical activity and decreased by moderate coffee consumption and hypertension. Smoking and old age increased the risk of trochanteric hip fracture. The LF ultrasound velocity reflected to some degree the geometry and bone mineral density of the proximal femur. Decreased low-frequency ultrasound velocity was a significant risk factor of hip fracture even when combined with lifestyle-related risk factors. The LF ultrasound method showed similar fracture discrimination ability compared to DXA and pQCT, especially on the radius. In conclusion, the LF ultrasound method showed promising results in bone characterization and fracture discrimination. Further prospective studies with larger population are needed to confirm the combined effect of clinical risk factors and LF ultrasound.