Now showing items 1-20 of 525

    • Pervasive blood pressure monitoring using Photoplethysmogram (PPG) Sensor

      Riaz, Farhan; Azad, Muhammad; Arshad, Junaid; Imran, Muhammad; Hassan, Ali; Rehmad, Saad; Derby (Elsevier, 2019-03-08)
      Preventive healthcare requires continuous monitoring of the blood pressure (BP) of patients, which is not feasible using conventional methods. Photoplethysmogram (PPG) signals can be effectively used for this purpose as there is a physiological relation between the pulse width and BP and can be easily acquired using a wearable PPG sensor. However, developing real-time algorithms for wearable technology is a significant challenge due to various conflicting requirements such as high accuracy, computationally constrained devices, and limited power supply. In this paper, we propose a novel feature set for continuous, real-time identification of abnormal BP. This feature set is obtained by identifying the peaks and valleys in a PPG signal (using a peak detection algorithm), followed by the calculation of rising time, falling time and peak-to-peak distance. The histograms of these times are calculated to form a feature set that can be used for classification of PPG signals into one of the two classes: normal or abnormal BP. No public dataset is available for such study and therefore a prototype is developed to collect PPG signals alongside BP measurements. The proposed feature set shows very good performance with an overall accuracy of approximately 95\%. Although the proposed feature set is effective, the significance of individual features varies greatly (validated using significance testing) which led us to perform weighted voting of features for classification by performing autoregressive modeling. Our experiments show that the simplest linear classifiers produce very good results indicating the strength of the proposed feature set. The weighted voting improves the results significantly, producing an overall accuracy of about 98%. Conclusively, the PPG signals can be effectively used to identify BP, and the proposed feature set is efficient and computationally feasible for implementation on standalone devices.
    • An efficient evolutionary user interest community discovery model in dynamic social networks for internet of people

      Jiang, Liang; Shi, Leilei; Lu, Liu; Yao, Jingjing; Yuan, Bo; Zheng, Yongjun; University of Derby (IEEE, 2019-01-17)
      Internet of People (IoP), which focuses on personal information collection by a wide range of the mobile applications, is the next frontier for Internet of Things (IoT). Nowadays, people become more and more dependent on the Internet, increasingly receiving and sending information on social networks (e.g., Twitter, etc.); thus social networks play a decisive role in IoP. Therefore, community discovery has emerged as one of the most challenging problems in social networks analysis. To this end, many algorithms have been proposed to detect communities in static networks. However, microblogging social networks are extremely dynamic in both content distribution and topological structure. In this paper, we propose a model EEUICD (Efficient Evolutionary User Interest Community Discovery) which employs a nature-inspired genetic algorithm to improve the quality of community discovery. Specifically, a preprocessing method based on HITS (Hypertext Induced Topic Search) improves the quality of initial users and posts, and a label propagation method is used to restrict the conditions of the mutation process to further improve the efficiency and effectiveness of user interest community detection. Finally, the experiments on the real datasets validate the effectiveness of the proposed model.
    • Petri net-based methods for analyzing structural security in e-commerce business processes

      Wangyang, Yu (Elsevier, 2018-05-30)
      The rapid development of e-commerce worldwide, means more e-commerce business processes adopting the structure of multiple participants; these include shopper clients, merchant and third-party payment platforms (TPPs), banks, and so on. It is a distributed and complex system, where communications among these participants rely on the web services and Application Programming Interfaces (APIs) such as Cashier-as-a-Service or CaaS. This introduces new security challenges due to complex interactions among multiple participants, and any design flaws in procedure structures may result in serious security issues. We study the structural security issues based on Petri nets, and a framework for analyzing structural security in e-commerce business process is proposed. Petri net-based modeling and analysis methods are also provided. Given the specifications of e-commerce business processes, the proposed methods can help designers analyze structural security issues of an e-commerce business process.
    • Multiplicity dependence of light-flavor hadron production in pp collisions at √s = 7 TeV

      Acharya, S.; Acosta, F. T.-.; Adamová, D.; Adler, A.; Adolfsson, J.; Aggarwal, M. M.; Aglieri Rinella, G.; Agnello, M.; Agrawal, N.; Ahammed, Z.; Ahn, S. U.; Aiola, S.; Akindinov, A.; Al-Turany, M.; Alam, S. N.; Albuquerque, D. S. D.; Aleksandrov, D.; Alessandro, B.; Alfanda, H. M.; Alfaro Molina, R.; Ali, Y.; Alici, A.; Alkin, A.; Alme, J.; Alt, T.; Altenkamper, L.; Altsybeev, I.; Anaam, M. N.; Andrei, C.; Andreou, D.; Andrews, H. A.; Andronic, A.; Angeletti, M.; Anguelov, V.; Anson, C.; Antičić, T.; Antinori, F.; Antonioli, P.; Anwar, R.; Apadula, N.; Aphecetche, L.; Appelshäuser, H.; Arcelli, S.; Arnaldi, R.; Arsene, I. C.; Arslandok, M.; Augustinus, A.; Averbeck, R.; Azmi, M. D.; Badalà, A.; Baek, Y. W.; Bagnasco, S.; Bailhache, R.; Bala, R.; Baldisseri, A.; Ball, M.; Baral, R. C.; Barbano, A. M.; Barbera, R.; Barile, F.; Barioglio, L.; Barnaföldi, G. G.; Barnby, L. S.; Barret, V.; Bartalini, P.; Barth, K.; Bartsch, E.; Bastid, N.; Basu, S.; Batigne, G.; Batyunya, B.; Batzing, P. C.; Bazo Alba, J. L.; Bearden, I. G.; Beck, H.; Bedda, C.; Behera, N. K.; Belikov, I.; Bellini, F.; Bello Martinez, H.; Bellwied, R.; Beltran, L. G. E.; Belyaev, V.; Bencedi, G.; Beole, S.; Bercuci, A.; Berdnikov, Y.; Berenyi, D.; Bertens, R. A.; Berzano, D.; Betev, L.; Bhaduri, P. P.; Bhasin, A.; Bhat, I. R.; Bhatt, H.; Bhattacharjee, B.; Bhom, J.; Bianchi, A.; Bianchi, L.; Bianchi, N.; Barnby, Lee; STFC Daresbury Laboratory (American Physical Society, 2019-02-08)
      Comprehensive results on the production of unidentified charged particles, π±, K±, K0S, K∗(892)0, p, p̅, ϕ(1020), Λ, Λ̅, Ξ−, Ξ̅+, Ω−, and Ω̅+ hadrons in proton-proton (pp) collisions at √s = 7 TeV at midrapidity (|y|<0.5) as a function of charged-particle multiplicity density are presented. In order to avoid autocorrelation biases, the actual transverse momentum (pT) spectra of the particles under study and the event activity are measured in different rapidity windows. In the highest multiplicity class, the charged-particle density reaches about 3.5 times the value measured in inelastic collisions. While the yield of protons normalized to pions remains approximately constant as a function of multiplicity, the corresponding ratios of strange hadrons to pions show a significant enhancement that increases with increasing strangeness content. Furthermore, all identified particle-to-pion ratios are shown to depend solely on charged-particle multiplicity density, regardless of system type and collision energy. The evolution of the spectral shapes with multiplicity and hadron mass shows patterns that are similar to those observed in p-Pb and Pb-Pb collisions at Large Hadron Collider energies. The obtained pT distributions and yields are compared to expectations from QCD-based pp event generators as well as to predictions from thermal and hydrodynamic models. These comparisons indicate that traces of a collective, equilibrated system are already present in high-multiplicity pp collisions.
    • ϒ suppression at forward rapidity in Pb–Pb collisions at √sNN=5.02TeV

      S., Acharya (Elsevier, 2018-11-12)
      Inclusive ϒ(1S) and ϒ(2S) production have been measured in Pb–Pb collisions at the centre-of-mass energy per nucleon–nucleon pair √sNN = 5.02 TeV, using the ALICE detector at the CERN LHC. The ϒ mesons are reconstructed in the centre-of-mass rapidity interval 2.5<y<4 and in the transverse-momentum range pT<15 GeV/c, via their decays to muon pairs. In this Letter, we present results on the inclusive ϒ(1S) nuclear modification factor RAA as a function of collision centrality, transverse momentum and rapidity. The ϒ(1S) and ϒ(2S) RAA, integrated over the centrality range 0–90%, are 0.37±0.02(stat)±0.03(syst) and 0.10±0.04(stat)±0.02(syst), respectively, leading to a ratio RAAϒ(2S)/RAAϒ(1S) of 0.28±0.12(stat)±0.06(syst). The observed ϒ(1S) suppression increases with the centrality of the collision and no significant variation is observed as a function of transverse momentum and rapidity.
    • Centrality and pseudorapidity dependence of the charged-particle multiplicity density in Xe–Xe collisions at √sNN = 5.44 TeV

      S., Acharya (2018-12-21)
      In this Letter, the ALICE Collaboration presents the first measurements of the charged-particle multiplicity density, dNch/dη, and total charged-particle multiplicity, Nchtot, in Xe–Xe collisions at a centre-of-mass energy per nucleon–nucleon pair of √sNN = 5.44 TeV. The measurements are performed as a function of collision centrality over a wide pseudorapidity range of −3.5<η<5. The values of dNch/dη at mid-rapidity and Nchtot for central collisions, normalised to the number of nucleons participating in the collision (Npart) as a function of √sNN follow the trends established in previous heavy-ion measurements. The same quantities are also found to increase as a function of Npart, and up to the 5% most central collisions the trends are the same as the ones observed in Pb–Pb at a similar energy. For more central collisions, the Xe–Xe scaled multiplicities exceed those in Pb–Pb for a similar Npart. The results are compared to phenomenological models and theoretical calculations based on different mechanisms for particle production in nuclear collisions. All considered models describe the data reasonably well within 15%.
    • Direct photon elliptic flow in Pb–Pb collisions at √sNN = 2.76 TeV

      S., Acharya (Elsevier, 2018-11-19)
      The elliptic flow of inclusive and direct photons was measured at mid-rapidity in two centrality classes 0–20% and 20–40% in Pb–Pb collisions at √sNN = 2.76 TeV by ALICE. Photons were detected with the highly segmented electromagnetic calorimeter PHOS and via conversions in the detector material with the e+e− pairs reconstructed in the central tracking system. The results of the two methods were combined and the direct-photon elliptic flow was extracted in the transverse momentum range 0.9<pT<6.2GeV/c. A comparison to RHIC data shows a similar magnitude of the measured direct-photon elliptic flow. Hydrodynamic and transport model calculations are systematically lower than the data, but are found to be compatible.
    • Measuring K0sK± interactions using pp collisions at √s=7 TeV

      S., Acharya (Elsevier, 2019-03-10)
      We present the first measurements of femtoscopic correlations between the KS0 and K± particles in pp collisions at √s=7 TeV measured by the ALICE experiment. The observed femtoscopic correlations are consistent with final-state interactions proceeding solely via the a0(980) resonance. The extracted kaon source radius and correlation strength parameters for KS0K− are found to be equal within the experimental uncertainties to those for KS0K+. Results of the present study are compared with those from identical-kaon femtoscopic studies also performed with pp collisions at √s=7 TeV by ALICE and with a KS0K± measurement in Pb–Pb collisions at √sNN=2.76 TeV. Combined with the Pb–Pb results, our pp analysis is found to be compatible with the interpretation of the a0(980) having a tetraquark structure instead of that of a diquark.
    • Mittag-Leffler state estimator design and synchronization analysis for fractional order BAM neural networks with time delays

      Pratap, A.; Dianavinnarasi, J.; Raja, R.; Rajchakit, G.; Cao, J.; Bagdasar, Ovidiu; University of Derby (Wiley InterScience, 2019-03-20)
      This paper deals with the extended design of Mittag-Leffler state estimator and adaptive synchronization for fractional order BAM neural networks (FBNNs) with time delays. By the aid of Lyapunov direct approach and Razumikhin-type method a suitable fractional order Lyapunov functional is constructed and a new set of novel sufficient condition are derived to estimate the neuron states via available output measurements such that the ensuring estimator error system is globally Mittag-Leffler stable. Then, the adaptive feedback control rule is designed, under which the considered FBNNs can achieve Mittag-Leffler adaptive synchronization by means of some fractional order inequality techniques. Moreover, the adaptive feedback control may be utilized even when there is no ideal information from the system parameters. Finally, two numerical simulations are given to reveal the effectiveness of the theoretical consequences.
    • Modeling emergent patterns of dynamic desert ecosystems

      Stewart, J.; Parsons, A. J.; Wainwright, J.; Okin, G. S.; Bestelmeyer, B. T.; Fredrickson, E. L.; Schlesinger, W. H.; University of Sheffield (Ecological Society of America, 2014-08-01)
      In many desert ecosystems, vegetation is both patchy and dynamic: vegetated areas are interspersed with patches of bare ground, and both the positioning and the species composition of the vegetated areas exhibit change through time. These characteristics lead to the emergence of multi-scale patterns in vegetation that arise from complex relationships between plants, soils, and transport processes. Previous attempts to probe the causes of spatial complexity and predict responses of desert ecosystems tend to be limited in their focus: models of dynamics have been developed with no consideration of the inherent patchiness in the vegetation, or else models have been developed to generate patterns with no consideration of the dynamics. Here we develop a general modelling framework for the analysis of ecosystem change in deserts that is rooted in the concept of connectivity and is derived from a detailed process-based understanding. We explicitly consider spatial interactions among multiple vegetation types and multiple resources, and our model is formulated to predict responses to a variety of endogenous and exogenous disturbances. The model is implemented in the deserts of the American Southwest both to test hypotheses of the causes of the invasion of woody shrubs, and to test its ability to reproduce observed spatial differences in response to drought in the 20th century. The model’s performance leads us to argue that vertical and lateral connectivity are key emergent properties of the ecosystem, which both control its behavior and provide indicators of its state. If this argument is shown to be compatible with field observations, the model presented here will provide a more certain approach toward preventing further degradation of semiarid grasslands.
    • Cascaded multimodal biometric recognition framework

      Albesher, Badr; Kurugollu, Fatih; Bouridane, Ahmed; Baig, Asim; Queen's University, Belfast (IET, 2013-08-15)
      A practically viable multi-biometric recognition system should not only be stable, robust and accurate but should also adhere to real-time processing speed and memory constraints. This study proposes a cascaded classifier-based framework for use in biometric recognition systems. The proposed framework utilises a set of weak classifiers to reduce the enrolled users’ dataset to a small list of candidate users. This list is then used by a strong classifier set as the final stage of the cascade to formulate the decision. At each stage, the candidate list is generated by a Mahalanobis distance-based match score quality measure. One of the key features of the authors framework is that each classifier in the ensemble can be designed to use a different modality thus providing the advantages of a truly multimodal biometric recognition system. In addition, it is one of the first truly multimodal cascaded classifier-based approaches for biometric recognition. The performance of the proposed system is evaluated both for single and multimodalities to demonstrate the effectiveness of the approach.
    • Privacy region protection for H.264/AVC with enhanced scrambling effect and a low bitrate overhead

      Wang, Yongsheng; O׳Neill, Máire; Kurugollu, Fatih; O׳Sullivan, Elizabeth; Queen's University, Belfast (Elsevier, 2015-05-12)
      While video surveillance systems have become ubiquitous in our daily lives, they have introduced concerns over privacy invasion. Recent research to address these privacy issues includes a focus on privacy region protection, whereby existing video scrambling techniques are applied to specific regions of interest (ROI) in a video while the background is left unchanged. Most previous work in this area has only focussed on encrypting the sign bits of nonzero coefficients in the privacy region, which produces a relatively weak scrambling effect. In this paper, to enhance the scrambling effect for privacy protection, it is proposed to encrypt the intra prediction modes (IPM) in addition to the sign bits of nonzero coefficients (SNC) within the privacy region. A major issue with utilising encryption of IPM is that drift error is introduced outside the region of interest. Therefore, a re-encoding method, which is integrated with the encryption of IPM, is also proposed to remove drift error. Compared with a previous technique that uses encryption of IPM, the proposed re-encoding method offers savings in the bitrate overhead while completely removing the drift error. Experimental results and analysis based on H.264/AVC were carried out to verify the effectiveness of the proposed methods. In addition, a spiral binary mask mechanism is proposed that can reduce the bitrate overhead incurred by flagging the position of the privacy region. A definition of the syntax structure for the spiral binary mask is given. As a result of the proposed techniques, the privacy regions in a video sequence can be effectively protected by the enhanced scrambling effect with no drift error and a lower bitrate overhead.
    • Theoretical investigation into balancing high-speed flexible shafts, by the use of a novel compensating balancing sleeve

      Knowles, Grahame; Kirk, Antony; Stewart, Jill; Bickerton, Ron; Bingham, Chris; University of Lincoln (IMechE, 2013-12-31)
      Traditional techniques for balancing long, flexible, high-speed rotating shafts are inadequate over a full range of shaft speeds. This problem is compounded by limitations within the manufacturing process, which have resulted in increasing problems with lateral vibrations and hence increased the failure rates of bearings in practical applications. There is a need to develop a novel strategy for balancing these coupling shafts that is low cost, robust under typically long-term operating conditions and amenable to on-site remediation. This paper proposes a new method of balancing long, flexible couplings by means of a pair of balancing sleeve arms that are integrally attached to each end of the coupling shaft. Balance corrections are applied to the free ends of the arms in order to apply a corrective centrifugal force to the coupling shaft in order to limit shaft-end reaction forces and to impart a corrective bending moment to the drive shaft that limits shaft deflection. The aim of this paper is to demonstrate the potential of this method, via the mathematical analysis of a plain, simply supported tube with uniform eccentricity and to show that any drive shaft, even with irregular geometry and/or imbalance, can be converted to an equivalent encastre case. This allows for the theoretical possibility of eliminating the first simply supported critical speed, thereby reducing the need for very large lateral critical speed margins, as this requirement constrains design flexibility. Although the analysis is performed on a sub 15 MW gas turbine, it is anticipated that this mechanism would be beneficial on any shaft system with high-flexibility/shaft deflection.
    • Blind image watermark detection algorithm based on discrete shearlet transform using statistical decision theory

      Ahmaderaghi, Baharak; Kurugollu, Fatih; Rincon, Jesus Martinez Del; Bouridane, Ahmed; Queen's University, Belfast (IEEE, 2018-01-15)
      Blind watermarking targets the challenging recovery of the watermark when the host is not available during the detection stage.This paper proposes Discrete Shearlet Transform (DST) as a new embedding domain for blind image watermarking. Our novel DST blind watermark detection system uses a non-additive scheme based on the statistical decision theory. It first computes the Probability Density Function (PDF) of the DST coefficients modelled as a Laplacian distribution. The resulting likelihood ratio is compared with a decision threshold calculated using Neyman-Pearson criterion to minimise the missed detection subject to a fixed false alarm probability. Our method is evaluated in terms of imperceptibility, robustness and payload against different attacks (Gaussian noise, Blurring, Cropping, Compression and Rotation) using 30 standard grayscale images covering different characteristics (smooth, more complex with a lot of edges and high detail textured regions). The proposed method shows greater windowing flexibility with more sensitive to directional and anisotropic features when compared against Discrete Wavelet and Contourlets.
    • Kinetic modelling of synaptic functions in the alpha rhythm neural mass model

      Basabdatta, Sen Bhattacharya; Coyle, Damien H; Maguire, Liam P; Stewart, Jill; University of Lincoln (Springer-Verlag Berlin Heidelberg, 2012)
      In this work, we introduce the kinetic framework for modelling synaptic transmission in an existing neural mass model of the thalamocortical circuitry to study Electroencephalogram (EEG) slowing within the alpha frequency band (8–13 Hz), a hallmark of Alzheimer’s disease (AD). Ligand-gated excitatory and inhibitory synapses mediated by AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid) and GABAA (gamma-amino-butyric acid) receptors respectively are modelled. Our results show that the concentration of the GABA neurotransmitter acts as a bifurcation parameter, causing the model to switch from a limit cycle mode to a steady state. Further, the retino-geniculate pathway connectivity plays a significant role in modulating the power within the alpha band, thus conforming to research proposing ocular biomarkers in AD. Overall, kinetic modelling of synaptic transmission in neural mass models has enabled a more detailed investigation into the neural correlates underlying abnormal EEG in AD.
    • Optimizing wide-area sound reproduction using a single subwoofer with dynamic signal decorrelation

      Hill, Adam J.; Moore, J.B.; University of Derby (Audio Engineering Society, 2019-03-10)
      A central goal in small room sound reproduction is achieving consistent sound energy distribution across a wide listening area. This is especially difficult at low-frequencies where room-modes result in highly position-dependent listening experiences. While numerous techniques for multiple-degree-of-freedom systems exist and have proven to be highly effective, this work focuses on achieving position-independent low-frequency listening experiences with a single subwoofer. The negative effects due to room-modes and comb-filtering are mitigated by applying a time-varying decorrelation method known as dynamic diffuse signal processing. Results indicate that spatial variance in magnitude response can be significantly reduced, although there is a sharp trade-off between the algorithm’s effectiveness and the resulting perceptual coloration of the audio signal.
    • Frontal view gait recognition with fusion of depth features from a time of flight camera

      Afendi Tengku Mohd; Kurugollu, Fatih; Crookes, Danny; Bouridane, Ahmed; Farid, Mohsen; Queen's University, Belfast; University of Derby; Northumbria University (IEEE, 2018-09-17)
      Frontal view gait recognition for people identification has been carried out using single RGB, stereo RGB, Kinect 1.0 and Doppler radar. However, existing methods based on these camera technologies suffer from several problems. Therefore, we propose a four-part method for frontal view gait recognition based on fusion of multiple features acquired from a Time of Flight (ToF) camera. We have developed a gait data set captured by a ToF camera. The data set includes two sessions recorded seven months apart, with 46 and 33 subjects respectively, each with six walks with five covariates. The four-part method includes: a new human silhouette extraction algorithm that reduces the multiple reflection problem experienced by ToF cameras; a frame selection method based on a new gait cycle detection algorithm; four new gait image representations; and a novel fusion classifier. Rigorous experiments are carried out to compare the proposed method with state-of-the-art methods. The results show distinct improvements over recognition rates for all covariates. The proposed method outperforms all major existing approaches for all covariates and results in 66.1% and 81.0% Rank 1 and Rank 5 recognition rates respectively in overall covariates, compared with a best state-of-the-art method performance of 35.7% and 57.7%.
    • Assessing Domain Specificity in the Measurement of Mathematics Calculation Anxiety

      Hunt, Thomas E.; Bagdasar, Ovidiu; Sheffield, David; Schofield, Malcolm B.; University of Derby (Hindawi, 2019-02-03)
      An online, cross-sectional approach was taken, including an opportunity sample of 160 undergraduate students from a university in the Midlands, UK. Exploratory factor analysis indicated a parsimonious, four-factor solution: abstract maths anxiety, statistics probability anxiety, statistics calculation anxiety, and numerical calculation anxiety. The results support previous evidence for the existence of a separate “numerical anxiety” or “arithmetic computation” anxiety component of maths anxiety and also support the existence of anxiety that is specific to more abstract maths. This is the first study to consider the multidimensionality of maths anxiety at the level of the calculation type. The 26-item Maths Calculation Anxiety Scale appears to be a useful measurement tool in the context of maths calculation specifically.
    • On some results concerning the polygonal polynomials.

      Andrica, Dorin; Bagdasar, Ovidiu; Babeș-Bolyai University; University of Derby (Technical University of Cluj-Napoca., 2019-02-13)
      In this paper we define the $n$th polygonal polynomial $P_n(z) = (z-1)(z^2-1)\cdots(z^n-1)$ and we investigate recurrence relations and exact integral formulae for the coefficients of $P_n(z)$ and for those of the Mahonian polynomials $Q_n(z)=(z+1)(z^2+z+1)\cdots(z^{n-1}+\cdots+z+1)$. We also explore numerical properties of these coefficients, unraveling new meanings for old sequences and generating novel entries to the Online Encyclopedia of Integer Sequences (OEIS). Some open questions are also formulated.
    • Behavioural Digital Forensics Model: Embedding Behavioural Evidence Analysis into the Investigation of Digital Crimes

      Al Mutawa, Noora; Bryce, Joanne; Franqueira, Virginia N. L.; Marrington, Andrew; Read, Janet C.; University of Derby (Elsevier, 2019-03)
      The state-of-the-art and practice show an increased recognition, but limited adoption, of Behavioural Evidence Analysis (BEA) within the Digital Forensics (DF) investigation process. Yet, there is currently no BEA-driven process model and guidelines for DF investigators to follow in order to take advantage of such an approach. This paper proposes the Behavioural Digital Forensics Model to fill this gap. It takes a multidisciplinary approach which incorporates BEA into in-lab investigation of seized devices related to interpersonal cases (i.e., digital crimes involving human interactions between offender(s) and victim(s)). The model was designed based on the application of traditional BEA phases to 35 real cases, and evaluated using 5 real digital crime cases - all from Dubai Police archive. This paper, however, provides details of only one case from this evaluation pool. Compared to the outcome of these cases using a traditional DF investigation process, the new model showed a number of benefits. It allowed a more effective focusing of the investigation, and provided logical directions for identifying the location of further relevant evidence. It also enabled a better understanding and interpretation of victim/offender behaviours (e.g., probable offenders' motivations and modus operandi), which facilitated a more in depth understanding of the dynamics of the specific crime. Finally, in some cases, it enabled the identification of suspect's collaborators, something which was not identified via the traditional investigative process.