Miracle-dz/UniFAR-FTUs huggingface dataset:
SPA: A Smart Packet Analyzer for Network Traffic Analysis on Smartphones

The intensifying growth of the internet and machinery whether its mobile or computer technology has brought countless good and proficient things for people such as E-commerce, E-mail, Cloud Computing, Data Sharing, Application and many more but there are also a dark and unseen sides of it such as Network Hacks, Computer hacks, Mobile Breach, Backdoors etc. In today’s era, Cybercrime been one of the communal practices made by the computer specialists and is growing swiftly in numbers. Network monitoring performance of mobiles or computer are becoming increasingly significant for the security protection within today’s organizational, ISP and carriers. There are the numerous tools which are available for network analysis, packet analysis such as Wireshark, Netresec, Termux. In this paper propose system is about an application idea through which user can analyze the network traffic, detect malicious packet, MAC spoofing, ARP spoofing, protocol filtering. Which will assist the user to identify the malicious packet that can cause damage to user’s assets.
Prediction and Visualisation of Bony Impingement for Subject Specific Total Hip Arthroplasty*

Bony impingement (BI) may contribute to restricted hip joint motion, and recurrent dislocation after total hip arthroplasty (THA), and therefore, should be avoided where possible. However, BI risk assessment is generally performed intra-operatively by surgeons, which is partially subjective and qualitative. Therefore, the aim of the study was to develop a method for identifying subject-specific BI, and subsequently, visualising BI area on native bone anatomy to highlight the amount of bone should be resected. Activity definitions and subject-specific bone geometries, constructed from CT scans, with planned implants were used as inputs for the method. For each activity, a conical clearance angle (CCA) was checked between femur and pelvis through simulation. Simultaneously, BI boundary and area were automatically calculated using ray intersection and region growing algorithm respectively. The potential use of the developed method was explained through a case study using an anonymised pre-THA patient data. Two pure (flexion, and extension) and two combined hip joint motions (internal and external rotation at flexion and extension respectively) were considered as activities. BI area were represented in two ways: (a) CCA specific where BI area for each activity with different CCAs was highlighted, (b) activity specific where BI area for all activities with a particular CCA was presented. Result showed that BI area between the femoral and pelvic parts was clearly identified so that the pre-operative surgical plan could be adjusted to minimise impingement. Therefore, this method could potentially be used to examine the effect of different preoperative plans and hip motion on BI, and to guide bony resection during THA surgery.
Photo Therapy Based Designed Device For Hyper-Pigmentation

Hyper-pigmentation is a disease in which brown colored spots appear on skin. Hyper-pigmentation occurs mainly due to excess production of Melanin. Melanin is a pigment that gives color to skin and produced by Melanocyte cells. This paper introduces a possible design and development of a phototherapy device whose intensity is controlled wirelessly. Near infrared optical radiations are applied to treat Hyper-pigmentation. The designed device consists of infrared Light Emitting Diode array of 830nm wavelength as emitter placed above an affected area. Intensity of LED array is controlled by the mobile phone.
A Temporal Data Analysis to Identify Land Cover Change Trends in NCT Delhi

Different types of land covers on the earth surface have different thermal characteristics and respond to solar heating and radiation cooling differently. Further the land covers emit heat in proportion to their respective temperatures and hence influence the air temperature differently. Therefore information about distribution and extent of various types of land covers along-with corresponding temperature has become important for environmental studies. Physical measurement of various land cover type or surface temperature at every place is not feasible. Fortunately advent of the remote sensing technology has considerably replaced the conventional ground surveys for a variety of data collection needs and providing even more precise data. The earth surface temperature estimates are now being derived from remotely captured data in thermal infrared band of the electromagnetic spectrum whereas land cover information is derived primarily from visible and near infrared bands. A time series data is taken mostly for three seasons of each year including spring, summer and post monsoon seasons to capture the seasonal variations and derive inclusive Land-use Land cover estimates on a five year periodicity since 1993. The time series LULC data is important for studying the correlation with the environment heating trends in the National Capital Territory and its contribution in the global warming. It would provide important inputs to the decision makers and other stake holders of NCT Delhi to set desired environmental standards and consider land-use planning to achieve the same in a conscious manner. As commonly believed, the study shows increase in the built up area at the expanse of vegetation cover. This work also redefines the approach of deriving ‘Land use Land cover’ from the Remote Sensing viewpoint to examine large scale real-spatial datasets.
Runtime-Environment Testing Method for Android Applications

One of the key problems in app testing is to improve the test coverage of apps. However, current testing techniques, whether in code coverage or activity coverage, are not satisfactory. To address this limitation, we present an algorithm for generating test runtime-environment-set to exercise mobile apps. Our approach is based on code analysis to systematically test the targeted code of the Android apps. It analyzes the decompiled code that identifies the code related to Android SDK version, generating the corresponding test cases with the runtime-environment set. We also implement our approach on Android, and validate the method with the existing widely used strategies. An empirical study of the practical usefulness of the technique has been presented on 6 widely-used industrial apps. 18 unique crashes have been found, and the method coverage has been increased by far 9.8% to 130.4% on those apps.
On the Realization of Self-Sensing Piezoelectric MEMS Actuators

Three different configurations of self-sensing piezoelectric MEMS actuators are designed, fabricated, and tested with PZT as the active material. A two-port circular diaphragm resonator of radius 1000 µm, a cantilever of length 1000 µm and width-24 µm with two parallel top electrodes, and a four-legged resonator structure with a proof mass of total die size 1.6 mm × 3 mm are fabricated and characterized as self-sensing actuators without any cross-talk compensation. A comparison among the output signals reveals that the cantilever (without etching the PZT in between the two electrodes) and the four-legged resonator perform well as self-sensing actuators, while the two-port diaphragm resonator with large concentric top electrodes suffers from electrical cross-talk. A successful characterization of a self-sensing actuator with the common ground electrode (for cantilever) is being reported for the first time. Deflection values of as low as 1 nm could be easily resolved using the proof-mass resonator. The act of actuation is verified by directly measuring the motion with laser doppler vibrometry which cross-verifies the sensor signal produced by the piezoelectric layer.
A Convolutional Neural Network-based Model of Neural Pathways in the Retina*

A variety of the visual functions of the vertebrate retina rely on the interactions between excitation and inhibition within specialized retinal circuitry. The nonlinear properties of these interactions, as well as a large number of cell types and pathways involved, pose a challenge for characterizing many of these retinal functions. To address these challenges, we develop a computational model in the convolutional neural network framework, along with an efficient, robust learning procedure that enables incorporating both excitatory and inhibitory interactions between the network layers of the retina through feedforward and lateral connections. The model successfully describes the spiking rate of retinal ganglion cells, for both real and simulated validation data. The recovered biologically-plausible model parameters represent the linear and nonlinear computations across retinal network layers. This novel model of retinal responses and the associated learning algorithm provide a powerful tool for understanding the complex visual computations in the retina and for replicating naturalistic visual functions of the retina for retinal prostheses applications.
An Electrocardiogram Delineator via Deep Segmentation Network*

Electrocardiogram (ECG) delineation is a process to detect multiple characteristic points, which contain critical diagnostic information about cardiac diseases. We treat the ECG delineation task as an one-dimensional segmentation problem, and propose a novel end-to-end deep learning method to segment sections of ECG signal. Our neural network consists of two parts: a segmentation network composed of multiple 1D Convolutional Neural Networks (CNN) and a postprocessing network composed of a sequential Conditional Random Field (CRF). Our method is trained and validated on QT database. The experimental results show that our method yields competitive overall performance compared with other state-of-the-art works and outperform them on onset of the P wave and offset of the T wave.
Formation,Evolution and Hydrocarbon-Controlling Geological Conditions of Major Paleohighs,Tarim Basin

The distribution, formation and evolution of paleohighs play a decisive role for hydrocarbon accumulation. Based on the seismic, log and test data, this paper systemically studies the distribution and evolution of different geological paleohighs in Tarim Basin. Through the comprehensive comparison of the properties and evolutional characteristics and hydrocarbon geological conditions of three paleohighs (Tazhong, Tabei and Bachu), it analyzes the favorable exploration domains during different periods, and indicates that the paleohigh in the crucial hydrocarbon-accumulation period and its later evolution impact on the basin's geological structure and restrict the hydrocarbon accumulation and distribution. These lead to different main controlling factors of hydrocarbons and different hydrocarbon accumulation zones in different periods. Tabei and Tazhong are the favorable accumulation areas in the late Caledonian period. These highs and their slopes of Tabei, Bachu, Tazhong, Tadong are the favorable accumulation areas in the late Hercynian period. In the Himalayan period, Bachu high and its ramp are the main favorable areas for exploration, and Tadong also deserves attention.
Optimización de un sistema de biorremediación de hidrocarburos a escala de laboratorio Optimization of a Hydrocarbon Bioremediation System at Laboratory Scale

The aim of this study was to optimize the parameters of moisture, temperature and ratio of nutrients to estimate the possibility of applying the technique of bioremediation in a soil contaminated with hydrocarbons. For this, an initial characterization of contaminated soil was made according to their physical and chemical characteris-tics and the number of heterotrophic and hydrocarbon degraders bacteria. Also the contaminant concentration by gravimetric method and by gas chromatography was studied. To optimize moisture and temperature, microcosms with moisture of 3%, 10%, 15% and 20% and temperatures of 5°C, 15°C, 28°C and 37°C were used. The monitoring of the mineralization of hydrocarbons was performed by measuring the CO 2 produced. To optimize the ratio of nutrients, di ﬀ erent microcosms were de-signed and were monitored by oxygen consumption and by determination of hydrocarbons by gas chromatography. The C:N:P relationships studied were 100:20:2, 100:10:1, 100:5:0,5 and 100:1:0,1. The results indicate that the mineralization of hydrocarbons was optimal for moisture of 10% to 20% and temperatures of 25°C to 37°C with CO 2 production values of 3000-4500 mgCO 2 kg- 1 . The optimal C:N:P ratio was 100:1:0,1 in which the highest oxygen consumption was and the elimina-tion of 83% of total hydrocarbons determined by gas chromatography with 78% and 89% of n-alkanes and polyaromatic hydrocarbons elimination, respectively.
Enhancing Trust –A Unified Meta-Model for Software Security Vulnerability Analysis

Over the last decade, a globalization of the software industry has taken place which has facilitated the sharing and reuse of code across existing project boundaries. At the same time, such global reuse also introduces new challenges to the Software Engineering community, with not only code implementation being shared across systems but also any vulnerabilities it is exposed to as well. Hence, vulnerabilities found in APIs no longer affect only individual projects but instead might spread across projects and even global software ecosystem borders. Tracing such vulnerabilities on a global scale becomes an inherently difficult task, with many of the resources required for the analysis not only growing at unprecedented rates but also being spread across heterogeneous resources. Software developers are struggling to identify and locate the required data to take full advantage of these resources. The Semantic Web and its supporting technology stack have been widely promoted to model, integrate, and support interoperability among heterogeneous data sources. This dissertation introduces four major contributions to address these challenges: (1) It provides a literature review of the use of software vulnerabilities databases (SVDBs) in the Software Engineering community. (2) Based on findings from this literature review, we present SEVONT, a Semantic Web based modeling approach to support a formal and semi-automated approach for unifying vulnerability information resources. SEVONT introduces a multi-layer knowledge model which not only provides a unified knowledge representation, but also captures software vulnerability information at different abstract levels to allow for seamless integration, analysis, and reuse of the modeled knowledge. The modeling approach takes advantage of Formal Concept Analysis (FCA) to guide knowledge engineers in identifying reusable knowledge concepts and modeling them. (3) A Security Vulnerability Analysis Framework (SV-AF) is introduced, which is an instantiation of the SEVONT knowledge model to support evidence-based vulnerability detection. The framework integrates vulnerability ontologies (and data) with existing Software Engineering ontologies allowing for the use of Semantic Web reasoning services to trace and assess the impact of security vulnerabilities across project boundaries. Several case studies are presented to illustrate the applicability and flexibility of our modelling approach, demonstrating that the presented knowledge modeling approach cannot only unify heterogeneous vulnerability data sources but also enables new types of vulnerability analysis.
Litter dynamics in different forest types suffered an extreme ice storm in the subtropical region,southern China

To understand the responses pattern of subtropical forests recovered from the damage of ice storm happened in southern China during Jan to Feb in 2008,we take three different forests,including coniferous forest,mixed forest and broad-leaf forest located in Tianjing Mountain,as a case to compare their differences in annual litter production,component and seasonal fluctuation in undamaged and damaged plots in each forest type and access their recuperability at the early stage of natural recovery.It is indicated that the annual input of litter in the damaged forests was up to 0.52 t? hm-2,3.21 t? hm-2 and 1.37 t? hm-2 in coniferous forest,broad-leaved forest and mixed forest,respectively.Compared with the normal annual amount of litter in subtropical forest of southern China,it is showed that the total input of litter decreased clearly,which came to 87.89%,53.46% and 76.78% in coniferous forest,broad-leaved forest and mixed forest,respectively.It is indicated that in the early recovery period,the severer damaged suffer,the less litter produce in the different forest type,which implied the broad-leaved forest has the best recuperability at the early stage of recovery.In addition,the change of components in litter illustrated that the proportion of leaf increased but the branches reduced after the ice storm attack in all forest type.In the case of seasonal fluctuation in litter among different forest type,the pattern between damaged forest and undamaged forest is similar in coniferous forest and broadleaved forest,but it is totally different in the mixed forest.Based on our conclusions,due to the higher resilience and best recuperability,the broad-leaved forest should be served as a preferential choice in forest management to decrease potential impacts of extreme ice storms in subtropical forests.
BUILDING MODEL RECONSTRUCTION WITH LIDAR DATA AND TOPOGRAPHIC MAP BY REGISTRATION OF BUILDING OUTLINES

This study integrates LiDAR data and topographic map information for reconstruction of 3D building models. The procedure includes feature extraction, registration and reconstruction. In this study, the tensor voting algorithm and a region-growing method with principal features are adopted to extract building roof planes and structural lines from LiDAR data. A robust least squares method is applied to register boundary points of LiDAR data with building outlines obtained from topographic maps. The registration accuracy is about 11 cm in both x- and y- coordinates. The results of the registration method developed here are satisfactory for the subsequent application. Finally, an actual LiDAR dataset and its corresponding topographic map information demonstrate the procedure for data fusion of automatic 3D building model construction.
Impacts of Glacial Reretreat on Runoff on Tibetan Plateau

On the Tibetan Plateau,there are more than 36 793 glaciers with an area of 49 873.44 km2 and volume of 4 561 km3. They account for 79.5% of the total glacial number,84% of the total glacial area and 81.6% of the total glacial volume in China. With the climate warming since the 20th century,particularly the rapid warming since the 1980 s,most glaciers are retreating. The first half of the century was characterized with a transition period from glacial advance to glacial retreat. The intensive retreat started from the 1950s to the 1960 s.There was stable or even advancing phenomena between the 1960s and the 1970 s. After the 1980 s,glacial retreat started again and became more intensive in the 1990s.There are more than 10 rivers originate from the Tibetan Plateau with the Asia's seven most important rivers including the Yongtze River,Yellow River,Ganges River,Indus River,Yarlung Zangbo River,Nujiang River. The runoffs of the seven rivers have shown an unstable changing with the retreat of the glaciers. They tend to increase,particularly in the winter half year because of more glacial meltwater supply. As glaciers continuously retreat,the amount of glacial meltwater would decrease at some stage; this would be especially true in the middle and small reaches.
Detecting Dynamic IP Addresses Using the Sequential Characteristics of PTR Records

Many cyberattacks are conducted using malware-infected hosts. Most of such malware-infected hosts comprise end-user devices, e.g., PCs, mobile devices, and IoT devices. In today’s Internet, the IP addresses of most end users are dynamic IP addresses that are allocated by Internet service providers (ISPs). Some countermeasures against cyberattacks use IP addresses as the unique indicators of infected hosts. However, the same dynamic IP address is not always reallocated to the same host owing to the settings and policies of ISPs. Therefore, detecting dynamic IP address blocks accurately is necessary to take appropriate countermeasures against cyberattacks. In conventional methods, dynamic IP address blocks are detected by matching a PTR record of the target IP address with predefined keywords that indicate dynamic allocation. However, these keywords do not always match the PTR records of dynamic IP addresses. Sometimes, they falsely match non-dynamic IP addresses. In this study, we propose a new method that detects dynamic IP address blocks more accurately and with a greater coverage than the conventional methods. Our method focuses on a unique feature of dynamic IP addresses: the PTR records of dynamic IP address blocks are sequentially configured by their administrators. The performance of our method was validated through evaluation using real and manually labeled data.
SANEAMIENTO Y DETOXIFICACIÓN DE CARNE DE LLAMA (Lama glama) INFECTADA CON Sarcocystis aucheniae MEDIANTE COCCIÓN, HORNEADO, FRITURA Y CONGELADO SANITATION AND DETOXIFICATION OF LAMA MEAT (LAMA GLAMA) INFECTED WITH

The aim of the study was the sanitation and disinfecting llama meat naturally infected with macrocysts of Sarcocystis aucheniae through any of four physical methods: boiling (100 oC for 10 min), baking (105 oC for 65 min), frying and freezing (-20 oC for 10 days). A lisis of macrocysts from treated and non-treated meats was prepared and inoculated (100 µg/kg of body weight, subcutaneously). into 30 rabbits of 4-5 months of age. Only rabbits of the positive control group (non-treated meat) died. Rabbits of the frozen meat group
Cognitive Processes, ICT, and Education: A Critical Analysis

Abstract Information and communication technologies (ICT) have brought about renewed spaces for the societies of today, full of possibility and transformation. Bordering on the infinite, these spaces have generated new activities and behaviors. This technological scenario is now commonplace, an everyday reality that has taken root in our lives with remarkable speed. Now would therefore be an appropriate time to open up a line of inquiry into how this is shaping educational practice and how it is affecting our cognitive structures. We have chosen to conduct a review of relevant literature that will enable us to adopt a critical analysis to our subject: education and, above all, the learner, seen from the perspective of neuroscience and social analysis. However, the principal aim of this paper is to lay bare the disparities between research findings and current educational practices that use ICT.