The Paradox of Choice: Investigating Selection Strategies for Android Malware Datasets Using a Machine-learning Approach

The increase in the number of mobile devices that use the Android operating system has attracted the attention of cybercriminals who want to disrupt or gain unauthorized access to them through malware infections. To prevent such malware, cybersecurity experts and researchers require datasets of malware samples that most available antivirus software programs cannot detect. However, researchers have infrequently discussed how to identify evolving Android malware characteristics from different sources. In this paper, we analyze a wide variety of Android malware datasets to determine more discriminative features such as permissions and intents. We then apply machine-learning techniques on collected samples of different datasets based on the acquired features’ similarity. We perform random sampling on each cluster of collected datasets to check the antivirus software’s capability to detect the sample. We also discuss some common pitfalls in selecting datasets. Our findings benefit firms by acting as an exhaustive source of information about leading Android malware datasets

Defining Traffic States using Spatio-temporal Traffic Graphs

Intersections are one of the main sources of congestion and hence, it is important to understand traffic behavior at intersections. Particularly, in developing countries with high vehicle density, mixed traffic type, and lane-less driving behavior, it is difficult to distinguish between congested and normal traffic behavior. In this work, we propose a way to understand the traffic state of smaller spatial regions at intersections using traffic graphs. The way these traffic graphs evolve over time reveals different traffic states - a) a congestion is forming (clumping), the congestion is dispersing (unclumping), or c) the traffic is flowing normally (neutral). We train a spatio-temporal deep network to identify these changes. Also, we introduce a large dataset called EyeonTraffic (EoT) containing 3 hours of aerial videos collected at 3 busy intersections in Ahmedabad, India. Our experiments on the EoT dataset show that the traffic graphs can help in correctly identifying congestion-prone behavior in different spatial regions of an intersection.Comment: Accepted in 23rd IEEE International Conference on Intelligent Transportation Systems September 20 to 23, 2020. 6 pages, 6 figure

Metal oxide semiconducting interfacial layers for photovoltaic and photocatalytic applications

The present review rationalizes the significance of the metal oxide semiconductor (MOS) interfaces in the field of photovoltaics and photocatalysis. This perspective considers the role of interface science in energy harvesting using organic photovoltaics (OPVs) and dye-sensitized solar cells (DSSCs). These interfaces include large surface area junctions between photoelectrodes and dyes, the interlayer grain boundaries within the photoanodes, and the interfaces between photoactive layers and the top and bottom contacts. Controlling the collection and minimizing the trapping of charge carriers at these boundaries is crucial to overall power conversion efficiency of solar cells. Similarly, MOS photocatalysts exhibit strong variations in their photocatalytic activities as a function of band structure and surface states. Here, the MOS interface plays a vital role in the generation of OH radicals, which forms the basis of the photocatalytic processes. The physical chemistry and materials science of these MOS interfaces and their influence on device performance are also discussed

Complex foot deformity and Illizarov technique: a record-based study

Background: Complex foot deformities may occur as a result of trauma, poliomyelitis, osteomyelitis, burn contractures, neuromuscular diseases or may present as a resistant congenital contracture such as clubfoot. The Ilizarov fixator is new and more efficient method in the treatment of orthopedic foot problems. The aim of the study was to assess the outcome of Illizarov technique.Methods: This is a hospital record-based study conducted in 32 patients of foot deformity at orthopedic ward of Navodaya Medical college and Hospital, Raichur.  The record- based data was collected in January to July 2019. Data analysis done with SPSS 24.0 version IBM USA.Results: Majority of the subjects were from 0 to 5 years age group i.e. 14 (43.8%). Mean age was 26.2±4.9 years. Majority in our study were males i.e. 71.9%. In majority of the cases, the cause of foot deformity was neglected and relapsed club foot i.e. 12 (37.5%). Treatment period was 22±7 weeks.   Conclusions: The Ilizarov method can successfully correct complex foot deformities. Success rate was 90.6%

Cinnarizinium picrate

In the title salt {systematic name: 4-diphenyl­methyl-1-[(E)-3-phenyl­prop-2-en-1-yl]piperazin-1-ium 2,4,6-trinitro­pheno­late), C26H29N2 +·C6H2N3O7 −, the cinnarizinium cation is protonated at the piperazine N atom connected to the styrenylmethyl group; the piperazine ring adopts a distorted chair conformaiton. In the crystal, bifurcated N—H⋯(O,O) hydrogen bonds link the components into two-ion aggregates

Wirelessly-Controlled Untethered Piezoelectric Planar Soft Robot Capable of Bidirectional Crawling and Rotation

Electrostatic actuators provide a promising approach to creating soft robotic sheets, due to their flexible form factor, modular integration, and fast response speed. However, their control requires kilo-Volt signals and understanding of complex dynamics resulting from force interactions by on-board and environmental effects. In this work, we demonstrate an untethered planar five-actuator piezoelectric robot powered by batteries and on-board high-voltage circuitry, and controlled through a wireless link. The scalable fabrication approach is based on bonding different functional layers on top of each other (steel foil substrate, actuators, flexible electronics). The robot exhibits a range of controllable motions, including bidirectional crawling (up to ~0.6 cm/s), turning, and in-place rotation (at ~1 degree/s). High-speed videos and control experiments show that the richness of the motion results from the interaction of an asymmetric mass distribution in the robot and the associated dependence of the dynamics on the driving frequency of the piezoelectrics. The robot's speed can reach 6 cm/s with specific payload distribution.Comment: Accepted to the 2023 IEEE International Conference on Robotics and Automation (ICRA

Defining Traffic States using Spatio-temporal Traffic Graphs

Intersections are one of the main sources of congestion and hence, it is important to understand traffic behavior at intersections. Particularly, in developing countries with high vehicle density, mixed traffic type, and lane-less driving behavior, it is difficult to distinguish between congested and normal traffic behavior. In this work, we propose a way to understand the traffic state of smaller spatial regions at intersections using traffic graphs. The way these traffic graphs evolve over time reveals different traffic states - a) a congestion is forming (clumping), the congestion is dispersing (unclumping), or c) the traffic is flowing normally (neutral). We train a spatio-temporal deep network to identify these changes. Also, we introduce a large dataset called EyeonTraffic (EoT) containing 3 hours of aerial videos collected at 3 busy intersections in Ahmedabad, India. Our experiments on the EoT dataset show that the traffic graphs can help in correctly identifying congestion-prone behavior in different spatial regions of an intersection. © 2020 IEEE

Diuretic activity of aqueous extract of roots of Cissampelos pareira in albino rats

Background: Diuretic compounds that stimulate the excretion of water with small traceable ions are potentially useful in most of disorders including those exhibiting edema such as congestive heart failure, nephritis, toxemia of pregnancy, premenstrual tension, and hypertension. The aim was to evaluate the diuretic activity of aqueous extract of roots of Cissampelos pareira (AQERCP) by Lipschitz method in albino rats.Methods: Five groups of Albino rats were used to evaluate the diuretic activity of AQERCP by using metabolic cages. The Group I serves as normal control received vehicle (carboxymethyl cellulose 2% in normal saline), the Group II furosemide (10 mg/Kg, p.o) in vehicle; other Groups III, IV, and V were treated with low (100 mg/kg), medium (200 mg/kg), and high (400 mg/kg) doses of AQERCP in vehicle. Immediately, after the extract treatment all the rats were hydrated with saline (15 ml/kg, p.o) and placed in the metabolic cages (3/cage), specially designed to separate urine and faeces, kept at 21°C±0.5°C.The total volume of urine collected was measured at the end of 5th hr. During this period, no food and water was made available to animals. Various parameters such as total urine volume and concentration of sodium, potassium, chloride ions in the urine were measured and estimated respectively.Results: In this model, when compared to vehicle treated control group the AQERCP at different dose levels (100, 200 and 400 mg/kg) has significantly increased the urine volume and also enhanced the elimination of sodium, potassium and chloride ions in urine.Conclusion: The results showed that single dose administration of AQERCP as 100, 200 and 400 mg/Kg and standard frusemide (10 mg/kg b.wt) has significantly (p<0.05*, p<0.01**, p<0.001***) increased the urine output along with an increase in concentration of sodium, potassium, and chloride. AQERCP 400 mg/Kg produced a greater diuretic activity, which is comparable to the effect of standard furosemide (10 mg/kg).The present study has supported and justified the basis for folklore use of roots of C. pareira as a diuretic agent

Black-box Adversarial Attacks in Autonomous Vehicle Technology

Despite the high quality performance of the deep neural network in real-world applications, they are susceptible to minor perturbations of adversarial attacks. This is mostly undetectable to human vision. The impact of such attacks has become extremely detrimental in autonomous vehicles with real-time "safety"concerns. The black-box adversarial attacks cause drastic misclassification in critical scene elements such as road signs and traffic lights leading the autonomous vehicle to crash into other vehicles or pedestrians. In this paper, we propose a novel query-based attack method called Modified Simple black-box attack (M-SimBA) to overcome the use of a white-box source in transfer based attack method. Also, the issue of late convergence in a Simple black-box attack (SimBA) is addressed by minimizing the loss of the most confused class which is the incorrect class predicted by the model with the highest probability, instead of trying to maximize the loss of the correct class. We evaluate the performance of the proposed approach to the German Traffic Sign Recognition Benchmark (GTSRB) dataset. We show that the proposed model outperforms the existing models like Transfer-based projected gradient descent (T-PGD), SimBA in terms of convergence time, flattening the distribution of confused class probability, and producing adversarial samples with least confidence on the true class. © 2020 IEEE