Heritage potential's mobilisation: challenges and development prospects the case of Guelma in Algeria

PurposeThe region of Guelma, located in the northeast of Algeria, is characterised by its important natural and cultural heritage. This heritage is ignored and abandoned, which leads to its degradation and even its disappearance. Thus, it is imperative to seek to know and understand the reasons for this situation. This study aims to reveal the constraints of heritage promotion and its staging through its insertion in the development process.Design/methodology/approachA hypothetical–deductive approach based on a qualitative method using surveys was carried out on the knowledge of the heritage of Guelma by the actors concerned. The laws and classification procedures were interpreted to identify the heritage's stakes to ensure sustainable local development through tourism.FindingsThe results show the lack of recognition of the natural and cultural heritage by the region's population, the cumbersome, long and complex classification procedure. The weakness of the offer in terms of tourist infrastructures constitutes a handicap to the valorisation of the heritage and prevents the enhancement and development of tourism. Systematically, heritage does not contribute to the local and territorial development of the Guelma region.Originality/valueThe article underlines the importance of raising awareness among the various heritage stakeholders and actors, and first, the population, of the value of their natural and cultural heritage to make it profitable and a driving force for local and territorial development.

On the dynamics and feasibility of transferred inference for diagnosis of invasive ductal carcinoma: A perspective

It is generally noticed that increasing the number of convolutional layers in generic image classification procedures proves to be detrimental to model performance in terms of validation accuracy and loss. Apart from vanilla CNNs, we have state-of-the-art (SOTA) architectures such as ResNet50 (and its variants) which show that through the use of skip-connections, higher performance metrics are attainable through deeper architectures. However, most evaluative metrics converge on a log scale as we go deeper with diminishing gradient of the metrics' curves. Given these two contrasting speculations, in this paper, we implement various vanilla and SOTA CNNs for the diagnosis of one of the most common forms of breast cancer - invasive ductal carcinoma (IDC) - to examine and understand the feasibility of implementation of SOTA CNNs through transferred weights when juxtaposed with vanilla CNNs (and LeNet-5) of varying configurations in terms of their performance metrics and other parameters. In this paper, we solve the dual-objective of studying behavioural aspects of avant-garde CNN models (more specifically, VGG16, VGG19, ResNet50, ResNet50V2, MobileNetV2, and DenseNet121) and proper diagnosis of IDC through intermediate neural activations to critically evaluate and theorize the performance of different models. We notice that among all the models, only VGG16, VGG19, LeNet-5 and a selected vanilla CNN through an optimization procedure were the ones to attain the best metrics, shared amongst them.

A graph-based framework for malicious software detection and classification utilizing temporal-graphs

In this paper we present a graph-based framework that, utilizing relations between groups of System-calls, detects whether an unknown software sample is malicious or benign, and classifies a malicious software to one of a set of known malware families. In our approach we propose a novel graph representation of dependency graphs by capturing their structural evolution over time constructing sequential graph instances, the so-called Temporal Graphs. The partitions of the temporal evolution of a graph defined by specific time-slots, results to different types of graphs representations based upon the information we capture across the capturing of its evolution. The proposed graph-based framework utilizes the proposed types of temporal graphs computing similarity metrics over various graph characteristics in order to conduct the malware detection and classification procedures. Finally, we evaluate the detection rates and the classification ability of our proposed graph-based framework conducting a series of experiments over a set of known malware samples pre-classified into malware families.

An Overview of Medical Imaging Techniques for Knee Osteoarthritis Disease

Osteoarthritis is the most common form of “Arthritis & Joint disease”. Osteoarthritis (OA) is one of the fundamental causes of older and overweight individual’s sickness. It is the main cause of disability in adults. Mostly this disease occurs in people above 45 years of age, in which women suffer more as compared to men. it is basically damaged the Cartilage, because of which bones rub each other causing intense pain and inflammation. this gets thick and makes spurs at the edges. The knee Osteoarthritis is of 4 grades according to X-ray. The first 2 grade and 3rd grade can be recovered with the help of therapy and medications, while the 4th grade is necessary for knee replacement. The emerging Osteoarthritis management approach involves clinical evaluation & diagnostic imaging techniques. Within this research, we explore descriptively and objectively the various medical imaging methods used to diagnose and identify knee osteoarthritis. We study on the automatically detection of recovery rate of human disease and classify Osteoarthritis in the knee from medical images (like Magnetic Resonance image, CT scan, X-ray) from various medical image classification procedures. This paper provides a study that focuses on the various medical imaging methods used to determine osteoarthritis.

IGHV-associated methylation signatures more accurately predict clinical outcomes of chronic lymphocytic leukemia patients than IGHV mutation load

Currently, no molecular biomarker indexes are used in standard care to make treatment decisions at diagnosis of chronic lymphocytic leukemia (CLL). We used Infinium MethylationEPIC array data from diagnostic blood samples of 114 CLL patients, and developed a patient stratification procedure based on methylation signatures associated with mutation load of the IGHV gene. This procedure allowed us to predict the time to treatment (TTT) with HR 8.34 (95% CI, 4.54-15.30), as opposed to HR 4.35 (95% CI, 2.60-7.28) for IGHV mutation status. Detailed evaluation of 17 discrepant cases between the two classification procedures showed that these cases were incorrectly classified using IGHV status. Moreover, methylation-based classification stratified patients with different overall survival (OS) (HR, 1.82; 95% CI, 1.07-3.09), which was not possible using IGHV status. Furthermore, we assessed the performance of the developed classification procedure using published HumanMethylation450 array data for 159 patients for which TTT, OS and relapse were available. Despite that 450K array methylation data did not contain all biomarkers used in our classification procedure, methylation signatures again stratified patients with significantly better accuracy than IGHV mutation load regarding all available clinical outcomes. Thus, stratification using IGHV-associated methylation signatures may provide improved prognostic power than IGHV mutation status.

A novel multi-classifier information fusion based on Dempster–Shafer theory: application to vibration-based fault detection

Achieving a high prediction rate is a crucial task in fault detection. Although various classification procedures are available, none of them can give high accuracy in all applications. Therefore, in this article, a novel multi-classifier fusion approach is developed to boost the performance of the individual classifiers. This is acquired by using Dempster–Shafer theory. However, in cases with conflicting evidences, the Dempster–Shafer theory may give counterintuitive results. In this regard, a preprocessing technique based on a new metric is devised in order to measure and mitigate the conflict between the evidences. To evaluate and validate the effectiveness of the proposed approach, the method is applied to 15 benchmarks datasets from UCI and KEEL. Furthermore, it is applied for classifying polycrystalline nickel alloy first-stage turbine blades based on their broadband vibrational response. Through statistical analysis with different noise levels, and by comparing with four state-of-the-art fusion techniques, it is shown that the proposed method improves the classification accuracy and outperforms the individual classifiers.

A Proposal to Classify and Assess Ecological Status in Mediterranean Temporary Rivers: Research Insights to Solve Management Needs

The biomonitoring methods implemented by water authorities are mostly developed for perennial rivers, and do not apply to temporary rivers (TRs). We propose a new classification for TRs to better assess their ecological status. It arises from the LIFE+ TRivers project, which was conducted in the Catalan and the Júcar Mediterranean river basin districts (RBD). The European Water Framework Directive (WFD) provided two systems to set river types (systems A or B from Annex II), which have been officially used by water authorities across Europe to set “national river types” (NRTs). However, essential hydrological variables for TRs are largely omitted. NRTs established according to the WFD were compared with TR categories obtained by using a rainfall-runoff model, “natural flows prescribed regimes” (NFPRs), and with “aquatic phases regimes” (APRs) calculated by using TREHS software. The biological quality indices currently used in Spain, based on macroinvertebrates and diatoms (IBMWP, IMMI-T, and IPS), were compared with a “general degradation” gradient in order to analyze the two TR river classification procedures (NFPR and APR). The results showed that NRTs did not properly classify TRs, and that the APR classification identified ecologically meaningful categories, especially those related to stagnant phases. Four “management temporary river categories” based on APRs are proposed to be used for water managers to properly assess the ecological status of TRs.

Assessment of kimberlite diamond grade by the indicator minerals chemical composition in Lunda region of Angola

<p>To determine a diamond grade (ct/t) in the Lunda district kimberlites using the chemical composition of the KIM (indicator minerals) frequency of occurrence of their cluster groups (CG) we performed statistical analysis of the chemical composition of pyropes (3478 grains) of Cr-diopsides (714) and picroilmenites (1582) of the 6 kimberlite diamond deposits. Classification procedures of cluster and correlation – factor analysis were used (Ivanov, 2017). Significant correlation coefficients were determined between the variations of KIM compositions and diamond content in kimberlites. Figure 2 shows the distribution of diamond contents in 6 kimberlite pipes, correlated with the distribution of pyropes G10 (Dawson et al., 1975), chromium diopsides CG S6, as well as CG of picroilmenites – 12b and P12-16 in their frequency of occurrence, the interpretation of which is reduced to the following conclusions. The proportions of pyropes CG G10 in kimberlites of 5 pipes control the linear growth (R<sup>2</sup>=0.97) of the diamond content in pipes to the center of the Saurimo structure, excluding the CAT-E42 pipe. With a relatively high diamond grade, the proportion of  G10 in this pipe is low, which may be related to the extremely low quality of its diamonds. In kimberlites. This indicator is typical for the Catoca and Luele pipes, with the maximum proportions of low-ferrous picroilmenites (11.0% and 13.9%). In the NE direction, the conditions for the preservation of diamonds in kimberlites decrease, which affects their low diamond grade (0.2-0.4 ct / t), which decreases exponentially (R<sup>2</sup>=0.98) with an increase in the TiO<sub>2</sub> content in picroilmenites. The proportion of CG S6 Cr-diopsides belonging to the high-pressure variety of the deep mantle lithosphere (coesite facies) (Sobolev, 1971) increases in the kimberlites of the central part of the Saurimo structure to 15-32% and controls the high diamond content of the Catoca, CAT-E42 and Luele pipes (Fig. 1). The established regularities of changes in the frequency of occurrence of CG KIMs in the NE-SW direction in the Lunda kimberlite region confirm the regional pyrope trend of N. V. Sobolev's diamond content and other KIMs correlations with the diamond content of kimberlites in this region. They also meet the "rule of V. A. Milashev" on reducing the diamond content of kimberlites to the periphery of regional structural units of kimberlite provinces (Zinchenko et al., 2016).</p><p>Sobolev N.V. Mineralogical criteria of diamond-bearing kimberlites. Geology and geophysics. No. 3. 1971, 70-80.</p><p>Dawson J.B., Stephens W.E. Statistical classification of garnets from kimberlites and xenoliths.J. Geol. 1975. 83, 589-60</p><p>Gurney D. D., Moore R. O. Geochemical correlation between kimberlite minerals and diamonds of the Kalahari Craton. 1994.,12–24.</p><p>Ivanov A. S. Statistical analysis of indicator minerals of kimberlites. Proceedings of the XIII All-Russian Fersman Session. KSC RAS.  Apatity. 2017,  172 -181.</p><p>Zinchenko, V., Felix J. T., Francisco J. Diamondiferous trend of the kimberlites in the Lunda region (Angola)//35th International Geological Congress Abstracts. Cape Town. South Africa. 2016.</p><p><img src="https://contentmanager.copernicus.org/fileStorageProxy.php?f=gnp.0e3eea868d0066419941161/sdaolpUECMynit/12UGE&app=m&a=0&c=7ecb3e7dd388e9edb98f52df0a9411a0&ct=x&pn=gnp.elif&d=1" alt="" width="581" height="346"></p><p><img src="https://contentmanager.copernicus.org/fileStorageProxy.php?f=gnp.960b89858d0069888941161/sdaolpUECMynit/12UGE&app=m&a=0&c=cdf3e97fdd49a7a10a2127127c90c0ff&ct=x&pn=gnp.elif&d=1" alt="" width="590" height="127"></p><p> </p>