Miracle-dz/UniFAR-FTUs huggingface dataset:
An Improved Network Intrusion Detection Based on Deep Neural Network

Network intrusion detection is of great significance for network security in Local Area Network (LAN). Traditional methods such as firewalls do not completely protect against attacks on the LAN due to lack of continuous learning. Recently, the ability of convolutional neural networks (CNN) to extract features in the field of computer vision has received extensive attention. CNN can automatically extract effective complex features to adapt to constantly changing environments, which is especially important in network intrusion detection. In this paper, we focus on network security in the LAN. We propose an approach based on CNN to implement intrusion detection in LAN. This approach can effectively identify network attacks and has an accuracy of 98.34% on the KDD99 dataset. The experimental results show that the proposed approach based on the CNN has high accuracy in intrusion detection.
Moving softly: the role of morphological computation in the generation of intelligent behaviour

The central theme of this thesis is ‘morphological computation’, in particular as it pertains to the generation of purposeful and intelligent behaviour. The first part of the thesis covers experiments in simulations, aimed at exploring a previously unasked question: can genuinely computational soft-body reservoirs play a central role in generating behaviour which has previously been described as ‘minimally cognitive’? We conclude in the affirmative, but also note that it remains unclear whether or how they can also exceed such abilities. The main part of this work has been presented at ALIFE 14 and ECAL 15, and published in the Artificial Life journal. In part two, the focus moves to consideration of how morphological computation in soft bodies may collude with the action of nervous systems in the production of adaptive intelligent behaviour. The massive and hypnotic complexity of brains in present day species, and lasting traditions in the design and control of animals’ mechanical analogies (robots), still lead many to perceive bodies in the neuromuscular species as being in service to the goals of their controllers (brains), but in fact the two are of a piece, and work together to the same ends. We hypothesise that this would have been more apparent than now at a time closer to the evolutionary introduction of neuromuscular systems, and introduce our new software framework for the evolution of virtual neuromuscular swimmers, which may be used to study artificial parallels to those distant origins. We begin with a demonstration of the technical innovations which we required in order to simulate soft-bodied swimmers in two-dimensional particle-based fluids, and then proceed to a description of our new concept for mapping arbitrary neural networks to arbitrary body morphologies.
Autoregressive Parameter Estimation for Equalizing Vibrotactile Systems

Musical performance, involving highly physical and cognitive expertise, can benefit from vibrotactile feedback systems offering independent control of amplitude and frequency of vibration over a wide frequency bandwidth. For advanced musical use, it is essential to perform the characterization of the amplifiers and actuators involved, as well as the equalization of their overall frequency response characteristics, a step typically implemented with the help of manually configured parametric equalizers. This paper proposes an autoregressive method that automatically estimates minimum- phase filter parameters, which by design, remain stable upon inver- sion. We demonstrate this method with an example implementation and discuss the degree of equalization achieved using it.
Towards continuous value delivery with review meetings in agile methodologies: A structured review

Continuous value delivery (CVD) is the practice to ensure the delivery of user and business value via a fast, reliable, and repeatable process. The change management lies at the core of CVD as the adjustments in value propositions often take place. Review meetings play an important role in change management because the review is a formal assessment with the intention of instituting change, if necessary. A thorough discussion of different agile methods in terms of review meetings as needed. Different papers were studied to extract the data regarding these meetings. It is observed that the sprint review meeting is important to the development team as it is an opportunity for the team to show its work explicitly and get appreciated. Development team spirits are increased by such environments. The sprint review establishes a firm level of sociable comparative competition between scrum teams that keeps everyone focused. It is actually equivalent to a user acceptance test. This paper discusses the importance of review meetings and their impact on CVD in well-known agile methods and using a structured review methodology. It evaluates the processes of review meetings such as planning, adaptability, integration in increment and reevaluation in well-known agile methods in order to find their effectiveness towards achieving CVD. It is found that Scrumban when strengthened with the EVO’s increment inspection process, can help in achieving CVD.
Modelling and Design of A 45nm SLC 3D NAND Flash CPLD

—With the impending end of Moore’s law in 2D silicon, there has been development on “more than Moore” technologies like 3D ICs in z-direction. We can stack silicon wafers to build and connect them with through silicon vias to make 3D ASICs as well as 3D FPGAs. However, this approach has lower manufacturing yield and reliability. Recent research has shown promises to make monolithic 3D ﬂash memories, which has revolutionized storage density in ﬂash memory devices. In this paper, we use the concept of monolithic 3D ﬂash memories to make small scale CPLDs using SLC NAND ﬂash architecture and show that the future of large scale FPGAs using NAND ﬂash architecture is promising. This paper shows circuit modelling of 3D CPLDs using modelled SLC NAND ﬂash bitcell and power, area and performance analysis. We further show the architecture of the 3D CPLDs using NAND ﬂash PLA planes and cross sectional details of the NAND string.
BPOP-v1 model: exploring the impact of changes in the biological pump on the shelf sea and ocean nutrient and redox state

Abstract. The biological pump of the ocean has changed over Earth's history, from one dominated by prokaryotes to one involving a mixture of prokaryotes and eukaryotes with trophic structure. Changes in the biological pump are in turn hypothesized to have caused important changes in the nutrient and redox properties of the ocean. To explore these hypotheses, we present here a new box model including oxygen (O), phosphorus (P) and a dynamical biological pump. Our Biological Pump, Oxygen and Phosphorus (BPOP) model accounts for two – small and large – organic matter species generated by production and coagulation, respectively. Export and burial of these particles are regulated by a remineralization length (zrem) scheme. We independently vary zrem of small and large particles in order to study how changes in sinking speeds and remineralization rates affect the major biogeochemical fluxes and O and P ocean concentrations. Modeled O and P budgets and fluxes lie reasonably close to present estimates for zrem in the range of currently measured values. Our results highlight that relatively small changes in zrem of the large particles can have important impacts on the O and P ocean availability and support the idea that an early ocean dominated by small particles was nutrient rich due to the inefficient removal of P to sediments. The results also suggest that extremely low oxygen concentrations in the shelf can coexist with an oxygenated deep open ocean for realistic values of zrem, especially for large values of the small-particle zrem. This could challenge conventional interpretations that the Proterozoic deep ocean was anoxic, which are derived from shelf and slope sediment redox data. This simple and computationally inexpensive model is a promising tool to investigate the impact of changes in the organic matter sinking and remineralization rates as well as changes in physical processes coupled with the biological pump in a variety of case studies.
Investigating mis-implementation of SSL libraries in android applications

This thesis presents our analysis of applications that are popular at the market against SSL miss-implementation. 8.882 applications analyzed and as a result 2.354 applications have at least one miss use of SSL libraries which are Custom TrustManager, Custom HostnameVeri ers and WebViewClient libraries. After analysis phase we have created a proof of concept application as an Xposed framework plugin to identify vulnerabilities. Our conclusion is that 27 percent of applications have a vulnerability from SSL connection stand point. The main reasons for these vulnerabilities are developer errors and third party generators or libraries. Using third party libraries can cause security bugs which leads to informations leakage or exploitation.
Development of the Community Water Model (CWatM v1.04) – a high-resolution hydrological model for global and regional assessment of integrated water resources management

Abstract. We develop a new large-scale hydrological and water resources model, the Community Water Model (CWatM), which can simulate hydrology both globally and regionally at different resolutions from 30 arcmin to 30 arcsec at daily time steps. CWatM is open source in the Python programming environment and has a modular structure. It uses global, freely available data in the netCDF4 file format for reading, storage, and production of data in a compact way. CWatM includes general surface and groundwater hydrological processes but also takes into account human activities, such as water use and reservoir regulation, by calculating water demands, water use, and return flows. Reservoirs and lakes are included in the model scheme. CWatM is used in the framework of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), which compares global model outputs. The flexible model structure allows for dynamic interaction with hydro-economic and water quality models for the assessment and evaluation of water management options. Furthermore, the novelty of CWatM is its combination of state-of-the-art hydrological modeling, modular programming, an online user manual and automatic source code documentation, global and regional assessments at different spatial resolutions, and a potential community to add to, change, and expand the open-source project. CWatM also strives to build a community learning environment which is able to freely use an open-source hydrological model and flexible coupling possibilities to other sectoral models, such as energy and agriculture.
Compliant activity rather than difficulty accelerates thought probe responsiveness and inhibits deliberate mind wandering

ABSTRACT Mind wandering is a commonly intruding cognitive state that leads to diminished performance and increased error risk during a primary task. A controversy over whether easier or more difficult tasks increase mind wandering has led to mind wandering being proposed as two different states: deliberate and spontaneous. We hypothesise that forced engagement via persistent compliant activity may both increase responsiveness and inhibit non-instrumental activities including deliberate mind wandering. Twenty-eight healthy adults interacted with 2 pairs of stimuli, each pair having one low-interactivity version and a high-interactivity version requiring compliant activity. Mind wandering was assessed by thought probes, and subjective responses were rated using visual analogue scales. Reaction times were measured using Superlab. Compliant activity decreased the prevalence of deliberate mind wandering episodes but not of overall mind wandering. Thought probe durations were accelerated significantly by compliant activity, near-significantly by thinking on-task thoughts, and additively by the combination of both. Deliberate and spontaneous mind wandering elicited equivalent thought probe durations. We conclude that compliant activity works synergistically with lack of mind wandering to accelerate the difficult task of thought probe response but not simple reaction times. These results fit with an arousal model but not the attentional resources model.
A Derivatives Trading Recommendation System: the Mid-Curve Calendar Spread Case

Derivative traders are usually required to scan through hundreds, even thousands of possible trades on a daily basis. Up to now, not a single solution is available to aid in their job. Hence, this work aims to develop a trading recommendation system, and apply this system to the so-called Mid-Curve Calendar Spread (MCCS). To suggest that such approach is feasible, we used a list of 35 different types of MCCS; a total of 11 predictive models; and 4 benchmark models. Our results suggest that linear regression with lasso regularisation compared favourably to other approaches from a predictive and interpretability perspective.
Analysis of Blind Source Separation Method for Weak Communication Signals Based on l2,1−RsPCA Algorithm

With the electromagnetic environment becoming more and more complicated, the signal received by the communication receiver always overlaps much noise and interference. The problem of the weak signal separation has gradually become more and more important. To solve this problem, we propose an algorithm called 2,1 RsPCA −  by combining some research results in the field of communication and mathematics. Through the separation experiment for random number and spread spectrum BPSK signal, we prove that the algorithm of 2,1 RsPCA −  can separate single-channel mixed signal effectively and outperforms some other classical algorithms
Toward Fast and Distributed Computation Migration System for Edge Computing in IoT

Code offload has been a key technique that provides new opportunities to achieve high performance with edge devices of weak computation capability. However, the implementation of code offload system on edge devices today is largely depending on backbone routers or cloud servers, imposes a significant burden on network traffic while ignores the potentials of utilizing Internet-of-Thing (IoT) devices physically nearby. In this article, we seek to obviate such limitations in improper code offload on edge devices, preferably focusing on minimizing interdomain data transfer and cross-device I/O cost while maximizing the CPU computation capability. First, we conduct the most in-depth and efficient analysis of both performance optimization and extra system burden. Second, we identify a new research problem of flexibly selecting the computation-intensive codes to offload at OS runtime across heterogeneous hardwares. Third, our measurement findings lead us to design and implement a fast and distributed code offload principle for edge devices called codeSpec, that shifts the destined devices from interdomain servers to IoT devices nearby, and only offloads binary code of user-specified regions across different instruction set architectures, thus to not only improve the system performance (by up to 80%) but also reduce burdens on data transfer (by at least 61%) and I/O latency (by on average 84%) than existing. codeSpec also makes user to flexibly specify the codes for offloading by plugging-in features, and is friendly to the commercial-off-the-shelf devices.
Monocular Visual Odometry for Fixed-Wing Small Unmanned Aircraft Systems

The popularity of small unmanned aircraft systems (SUAS) has exploded in recent years and seen increasing use in both commercial and military sectors. A key interest area for the military is to develop autonomous capabilities for these systems, of which navigation is a fundamental problem. Current navigation solutions suffer from a heavy reliance on a Global Positioning System (GPS). This dependency presents a significant limitation for military applications since many operations are conducted in environments where GPS signals are degraded or actively denied. Therefore, alternative navigation solutions without GPS must be developed and visual methods are one of the most promising approaches. A current visual navigation limitation is that much of the research has focused on developing and applying these algorithms on ground-based vehicles, small hand-held devices or multi-rotor SUAS. However, the Air Force has a need for fixed-wing SUAS to conduct extended operations. This research evaluates current state-of-the-art, open-source monocular visual odometry (VO) algorithms applied on fixed-wing SUAS flying at high altitudes under fast translation and rotation speeds. The algorithms tested are Semi-Direct VO (SVO), Direct Sparse Odometry (DSO), and ORB-SLAM2 (with loop closures disabled). Each algorithm is evaluated on a fixed-wing SUAS in simulation and realworld flight tests over Camp Atterbury, Indiana. Through these tests, ORB-SLAM2 is found to be the most robust and flexible algorithm under a variety of test conditions. However, all algorithms experience great difficulty maintaining localization in the collected real-world datasets, showing the limitations of using visual methods as the sole solution. Further study and development is required to fuse VO products with additional measurements to form a complete autonomous navigation solution.
On the impact of mobility in cellular networks

It is well-known that mobility increases the throughput of wireless networks, and the main objective of this paper is to show that, depending on the system's parameters, delay can actually be negatively impacted. To do so, we study a Markovian model where users arrive to the network according to a Poisson process with rate $\lambda$ and then move at speed $\alpha \ \epsilon [0, \infty)$ between nodes while in service. Given the complexity of the model, we resort to approximation techniques in order to get insight into the influence of the speed $\alpha$ on the mean delay. Our main findings are the following: •in the case where the network consists of two nodes, delay is monotone in $\alpha$ for small values of $\lambda$. We furthermore explicit a constant $C$ such that delay is increasing if and only if $C < 0$; •in the general case, we provide numerical results showing that delay is not necessarily monotone in $\alpha$. However, we compare the two extreme cases with 0 and infinite speed, and find that for small values of $\lambda$, delay is worse with infinite speed than with 0 speed if and only if $C < 0$. Finally, an intuitive interpretation of this constant $C$ is provided.
THE CONCEPT OF HALAL IN VISUAL ART MARKETING STRATEGY: A RESEARCH MODEL DEVELOPMENT

Visual art marketing strategy is a crucial aspect to be taken into consideration in order to ensure the continuous development of visual art field. It assists visual art practitioners to keep being productive in their efforts to come out with more art pieces to be sold. A few previous researches featured several marketing strategies for visual arts: nevertheless, there is no attempt to look at visual art marketing from the perspective of Islamic shariah. With uncertainties looming on visual art’s place in marketing world, the researchers recognize the need to study the concept of Islamic shariah in visual art marketing strategies. Based on this identified research gap, this study aims to produce a model that is related to the Islamic shariah concept regarding visual art marketing strategies. As a result, the discussion on the model involves several aspects namely: 1) product; 2) production process; 3) market place; 4) retailer / collectors; and 5) transactions. Recommendation for future research direction in this area is a more comprehensive study on Islamic marketing strategies in visual art.
Towards a Reliable Intrusion Detection Benchmark Dataset

The urgently growing number of security threats on Internet and intranet networks highly demands reliable security solutions. Among various options, Intrusion Detection (IDSs) and Intrusion Prevention Systems (IPSs) are used to defend network infrastructure by detecting and preventing attacks and malicious activities. The performance of a detection system is evaluated using benchmark datasets. There exist a number of datasets, such as DARPA98, KDD99, ISC2012, and ADFA13, that have been used by researchers to evaluate the performance of their intrusion detection and prevention approaches. However, not enough research has focused on the evaluation and assessment of the datasets themselves and there is no reliable dataset in this domain. In this paper, we present a comprehensive evaluation of the existing datasets using our proposed criteria, a design and evaluation framework for IDS and IPS datasets, and a dataset generation model to create a reliable IDS or IPS benchmark dataset.
Study of the Smoothing effect on the power production in an array of SEAREV wave energy converters.

This paper deals with the smoothing effect on power production in an array of SEAREV wave energy converters (WEC) due to the summation of each single converter’s production. A numerical model of the SEAREV WEC developed in previous works is used in this study to perform numerical simulations of motions of each WEC in the array in order to compute the full energy production. Comparisons are made between the electricity produced by each single device and the array. It shows the benefit of this smoothing effect on the global energy production. In monodirectionnal random waves, results show only a few devices are needed in order to reduce strongly the standard deviation of the instantaneous power with the mean power. Several device layouts are also considered, for different sets of random directional waves. It is shown that the smoothing effect does not depend on the sea state conditions nor on the layout of the array but only on the number of systems in the array.