External Indices Research Articles

Grievance-fueled violence can be better understood using an enactive approach.

Understanding lone actor grievance-fueled violence remains a challenge. We believe that the concept of grievance provides an opportunity to add an engaged, first-person perspective to the assessment of lone actor extreme violence. We propose an enactivist philosophical approach that can help to understand the why and how of the pathway from grievance to violent extremism. Enactivism sees grievance as a dynamic, interpersonal, and context-sensitive construct that indicates how (potential) offenders make sense of the world they live in and how under certain circumstances it fuels violent behavior. Hence, grievance should not be understood as a given thing, but as an unfolding experience that involves sense-making through (regulation of one's) interaction with the (social) environment. This (self-)relational and ecological understanding requires another approach than looking at demographic factors or life histories, only from an outsider's perspective. Enactivism invites us to look at such risk factors as external indices of an ongoing process of active self-regulation and sense-making, and in some cases spiraling toward extreme violence. To understand the mindset of the offender we need to look more in depth at the processes that shape this mindset: why does this person, with this history, in this context, and at this point in time, proceed to use violence? The enactivist approach to the mind offers a complementary framework that may help us to understand the dynamics of grievance as a possible precursor to violent extremism. It also helps to appreciate why the relative unpredictability of the pathway toward lone actor extreme violence is not necessarily a sign of empirical weakness but a matter of principle due to the non-linearity of the processes involved. We end by summarizing how enactivism could contribute to the prevention of extremist violence and research and how it can help to avoid reinforcing stigmas and re-establishing a confirmation bias.

Use of caliper-based external measurement of body surface in assessing the severity of pectus excavatum.

IntroductionObjective assessment of the severity of pectus excavatum (PE) mainly depends on internal imaging examination, which poses radiation exposure risks and high financial costs. Our study explores the feasibility of caliper-based external measurements of the body surface to assess PE severity.Materials and methodsPatients with PE aged 4–18 years who underwent both internal imaging examinations and external measurements were chosen for the study. Overall, 176 patients underwent surgery and 21 underwent regular observation. The Haller index (HI) and correction index (CI) were used to derive the external measurement indices, HI-caliper and CI-caliper. Receiver-operator characteristic analysis provided the optimal cut-off values and compared the diagnostic values of HI-caliper and CI-caliper. Spearman's correlation coefficient and Cohen's kappa coefficient were used to analyze the correlation and consistency between HI-caliper or CI-caliper and HI-CT or CI-CT, respectively. Also, a paired samples t-test was used to compare the differences of HI-caliper or CI-caliper before and after surgery.ResultsHI-caliper and CI-caliper measurements had strong correlations with HI-CT and CI-CT results (rs = 0.70, p < 0.001; rs = 0.69, p < 0.001), respectively. The optimal cut-off values of HI-caliper and CI-caliper were 1.83 (sensitivity = 0.841, specificity = 0.905) and 12% (sensitivity = 0.881, specificity = 0.857), exhibiting comparable diagnostic values with HI-CT and CI-CT. HI-caliper > 1.83 or CI-caliper > 12% had medium intensity consistency with HI-CT ≥ 3.25 or CI-CT ≥ 28% (k = 0.545, 95% confidence interval: 0.374–0.716, p < 0.001). The HI-caliper and CI-caliper values were significantly different before and after surgery.ConclusionCaliper-based external measurement is a feasible method to screen patients who require surgical intervention and for monitoring the progression of PE severity.

Determining of radioactivity and the accompanying radiological hazards in the sediments of the Euphrates River and wells in Babylon governorate – Iraq

The radioactivity and radiological hazards associated with sediment samples collected from 13 locations along the Euphrates River as well as 12 associated irrigation wells were tested using a high-purity germanium system (HPGe). The radioactivity of isotopes 226Ra, 232Th, and 40K (Iso-RTK) in these sites exceed the worldwide limits, which makes them a human health risk. The estimated radiological parameters of the Euphrates and the well sediments exceed the radium equivalent (RE), absorbed dose rate (ADR), annual effective dose external (AEDE), internal - external hazards indices (IEHI), , and gamma index (Iy) . The radioactivity ​​of 238U and 232Th (Iso-UT) are constant along the Euphrates River; 40K (Iso-K) concentrations are elevated after the Hindyia barrage and exceed worldwide limits.

Distribution of Radionuclides and Radiological Health Assessment in Seih-Sidri Area, Southwestern Sinai.

The current contribution goal is to measure the distribution of the radionuclide within the exposed rock units of southwestern Sinai, Seih-Sidri area, and assess the radiological risk. Gneisses, older granites, younger gabbro, younger granites, and post granitic dikes (pegmatites) are the main rock units copout in the target area. Radioactivity, as well as radiological implications, were investigated for forty-three samples from gneisses (seven hornblende biotite gneiss and seven biotite gneiss), older granites (fourteen samples), and younger granites (fifteen samples of syenogranites) using NaI (Tl) scintillation detector. External and internal hazard index (Hex, Hin), internal and external level indices (Iα, Iγ), absorbed dose rates in the air (D), the annual effective dose equivalent (AED), radium equivalent activity (Raeq), annual gonadal dose (AGDE), excess lifetime cancer risk (ELCR), and the value of Upper Continental Core 232Th/238U mass fractions were determined from the obtained values of 238U, 232Th and 40K for the examined rocks of Seih-Sidri area. The average 238U mg/kg in hornblende biotite gneiss and biotite gneiss, older granites, and syenogranites is 2.3, 2.1, 2.7, and 8.4 mg/kg, respectively, reflecting a relatively higher concentration of uranium content in syenogranites. The results suggest that using these materials may pose risks to one’s radiological health.

Collaborative annealing power [formula omitted]-means++ clustering

Clustering is the most fundamental technique for data processing. This paper presents a collaborative annealing power k-means++ clustering algorithm by integrating the k-means++ and power k-means algorithms in a collaborative neurodynamic optimization framework. The proposed algorithm starts with k-means++ to select initial cluster centers, then leverages the power k-means to find multiple sets of centers as alternatives and a particle swarm optimization rule to reinitialize the centers in the subsequential iterations for improving clustering performance. Experimental results on twelve benchmark datasets are elaborated to demonstrate the superior performance of the proposed algorithm to seven mainstream clustering algorithms in terms of 21 internal and external indices.

Research on the success of unsupervised learning algorithms in indoor location prediction

With location-based smart applications, the flow of life can be facilitated and support can be provided in case of security and emergency situations. Indoor location detection provides various conveniences in complex structures such as hospitals, schools, shopping centers, etc. Indoor location detection studies are carried out by using data related to location and signal and machine learning methods. Machine learning has become frequently used as a solution method in this field, as in many other fields. When the studies in the literature are examined, it is seen that the studies are mainly focused on producing solutions with supervised machine learning algorithms. Unsupervised algorithms are frequently used to determine the labels of data groups that do not have labels. In this direction, it can be seen as the first step in labeling the data collected in indoor positioning studies and then using it for training predictive models to be developed with supervised learning methods. For this reason, the results to be obtained regarding the success and usefulness of cluster analysis will constitute an important basis for further studies. In this study, it is aimed to examine the success of unsupervised learning, in other words, clustering algorithms. The Wireless Indoor Localization Data Set and well-known k-Means and Fuzzy c-Means algorithms have been used with different distance measure. The obtained methods performances have been evaluated with internal and external indices. The results show that the clustering algorithms can cluster correctly data points in the range of 93-95% according to the accuracy and F measure value. Although performances indicators are very close to each other according to the internal indexes, it can be stated that the model obtained using the Manhattan distance measure and the k-Means algorithm has higher performance in terms of clustering success.

Market Efficiency and Cross-Correlations of Chinese New Energy Market with Other Assets: Evidence from Multifractality Analysis.

Despite the upgrading of the attention and investment of new energy in Chinese public, its market efficiency and associations with other assets are relatively rarely explored. This paper, firstly, explores the multifractal feature and market efficiency of Chinese new energy market (NEI) by the multifractal detrended fluctuation analysis. Secondly, the multifractal cross-correlation analysis is performed to discuss the multifractality of cross-correlations between NEI and crude oil, external new energy indices (Global (SPGCE), United States (ECO) and Europe (ERIX)) and safe-haven asset (GOLD) respectively. The results show that Chinese new energy market has obvious multifractality with low market efficiency, which is mainly sourced from long-range correlation. It has the strongest linkages with external new energy markets and most insignificant association with gold. The heterogeneous sources contribute to their multifractal cross-correlations. It provides useful enlightenment for decision-makers to implement energy policy and reform, and for investors to make investment decisions.

Understanding the Adjusted Rand Index and Other Partition Comparison Indices Based on Counting Object Pairs

In unsupervised machine learning, agreement between partitions is commonly assessed with so-called external validity indices. Researchers tend to use and report indices that quantify agreement between two partitions for all clusters simultaneously. Commonly used examples are the Rand index and the adjusted Rand index. Since these overall measures give a general notion of what is going on, their values are usually hard to interpret. The goal of this study is to provide a thorough understanding of the adjusted Rand index as well as many other partition comparison indices based on counting object pairs. It is shown that many overall indices based on the pair-counting approach can be decomposed into indices that reflect the degree of agreement on the level of individual clusters. The decompositions (1) show that the overall indices can be interpreted as summary statistics of the agreement on the cluster level, (2) specify how these overall indices are related to the indices for individual clusters, and (3) show that the overall indices are affected by cluster size imbalance: if cluster sizes are unbalanced these overall measures will primarily reflect the degree of agreement between the partitions on the large clusters, and will provide much less information on the agreement on smaller clusters. Furthermore, the value of Rand-like indices is determined to a large extent by the number of pairs of objects that are not joined in either of the partitions.

COMPARATIVE ANALYSIS OF CLUSTER VALIDITY INDICES IN TERMS OF CONSISTENCY

Cluster analysis is one of the key issues in Data Mining, the most important stage of the Knowledge Discovery from Data (KDD) process, and is widely used. There are 3 main tasks of cluster analysis: determining the optimal number of clusters, clustering algorithms and evaluating the quality of clustering. One of the most important steps in cluster analysis is to evaluate the quality of clustering. A number of indices have been proposed to assess the outcome of clustering. The analysis shows that these indices, which are used to assess the quality of clustering, often show inconsistent results. Therefore, extensive research has recently been conducted on the study of indices and new indices are proposed. The article examines a number of internal and external evaluation indices. Different size data sets are taken and k-means, k-medoids, agglomerative hierarchical, BIRCH and OPTICS algorithms are applied to them. A number of internal and external evaluation indices are used to assess the results of the experiment, and the results are analyzed comparatively. Experiments show that Ac, Pr, Rc and F-m indices show similar results in in group determining in a given clustering structure.

Contexts of Concealment: Initial Validation of Three Disclosure Avoidance Process Measures

The choice to withhold subjective distress reflects a multifactorial decision highly sensitive to context. Unfortunately, existing measures are built on unidimensional models (i.e., concealment-disclosure as a single, bipolar dimension) and operationalize the construct as a stable trait. In this article, we outline the development and initial validation of a self-report inventory that accounts for problem-context and assesses multiple processes central to both the concealment and disclosure of emotional distress. Exploratory analysis of pilot items in Study 1 (male student sample; N = 373) guided subsequent item development and revisions to our conceptual model. In Study 2 (mixed-gender community sample; N = 297), we refined the item-pool based on additional tests of latent scale structure and associations with concurrent criteria. In a final validation sample (Study 3; international community participants; N = 978), confirmatory factor analyses corroborated our hypothesized three-factor model (Privacy Management, Disclosure Desire, and Social Fear) and supported measurement invariance by sex. The three Contexts of Concealment Scales (CCS) were internally consistent and associated in expected directions with external indices of concurrent concealment, disclosure, depression, anxiety, loneliness, experiential avoidance, and self-stigma.

Railway Fault Text Clustering Method Using an Improved Dirichlet Multinomial Mixture Model

Railway signal equipment fault data (RSEFD) are one of the issues with in-depth traffic big data analysis throughout the life cycle of intelligent transportation. In the course of daily operation and maintenance, the railway electrical maintenance department records equipment malfunction information in a natural language. The data have the characteristics of strong professionalism, short text, unbalanced category, and low efficiency of manual analysis and processing. How to effectively mine the information contained in these fault texts to provide help for on-site operation and maintenance plays an important role. Therefore, we propose a railway fault text clustering method using an improved Dirichlet multinomial mixture model called ICH-GSDMM. In this method, first, the railway signal terminology thesaurus is established to overcome the inaccurate problem of RSEFD segmentation. Second, the traditional Chi square statistics is improved to overcome the learning difficulties caused by the imbalance of RSEFD. Finally, the Gibbs sampling algorithm for Dirichlet multinomial mixture model (GSDMM) is modified using an improved chi-square statistical method (ICH) to overcome the symmetry problem of the word Dirichlet prior parameters in the traditional GSDMM. Compared to the traditional GSDMM model and the GSDMM model based on chi-square statistics (CH-GSDMM), the quantitative experimental results show that the GSDMM model based on improved chi-square statistics (ICH-GSDMM internal)’s evaluation index of clustering performance has greatly improved, and its external evaluation indices are also the best, with the exception of external index NMI of data set DS2. Simultaneously, the diagnostic accuracy of a select few categories in RSEFD has considerably improved, demonstrating its efficacy.

Measuring of natural and artificial radioactivity in Al-Dakhiliya governorate, Sultanate of Oman

Soil and sand samples were collected from eight different locations in the Al-Dakhiliya governorate, Sultanate of Oman to determine and evaluate the natural and artificial radioactivity levels. The activity concentrations of radionuclides 137Cs, 226Ra, 40K, 235U and 228Ac were measured using high resolution gamma-ray spectroscopy detectors (HPGe detectors). In addition, radiation hazard indexes were evaluated in order to measure radioactive risk for human beings and the environment. The activity concentrations of 137Cs, 226Ra, 40K, 235U and 228Ac were found as 0.82 ± 0.04, 29.01 ± 1.37, 290.14 ±2.79, 5.88 ± 0.65 and 39.57 ± 3.85 Bq/Kg respectively. Radium-equivalent activity Raeq was obtained and varied in the range from 340 to 43 Bq/Kg with a mean value of 108.3 Bq/Kg. The study found that the gamma indexes, external indexes and internal indexes in most sites were less than 1, which indicates a low radioactive dose. The study concludes that seven sites contain relatively low radioactivity, whereas one site requires more investigation in future as the results show a sort of rise in the radioactivity rate on its samples.

Radiation evaluation of household appliances and stone materials from residences in Hangzhou

The electromagnetic radiation of household appliances and radioactivity of stone materials from residences were determined using integrated magnetometer and γ-ray spectrometer techniques. The radiation levels of desktop computers were greater than that of notebook computers, while microwave ovens and induction cookers produced low-frequency electromagnetic fields during the operation. The safety distances for hair drier, desk lamp, and patch board were ca. 50 cm, whereas those of the rest appliances were ca. 30 cm. Radioactive tests of stones collected from certain regions were conducted. The specific activities of 226Ra, 232Th, and 40K were used to calculate internal exposure indexes (I Ra) and external exposure indexes (I γ). Moreover, both the I Ra and I γ for wall coatings were putty < tile adhesive, thereby the I Ra and I γ for bathroom furniture were ceramic facet < pottery basin < flush toilet. Natural radionuclides widely exist in interior decorations, indicating that humans in open radioactive environments receive background radiation all the time.

External Sector Macroeconomic Indices and Real Economy of Nigeria: An Empirical Analysis (1981 – 2020)

In recent times, the external sector of Nigeria’s economy has been characterized by instability, while the performance of her Real Economic Growth (RGDP) has remained below average. This study, therefore, investigated the relationship between her (RGDP), and some external sector macroeconomic indices, namely: Foreign Exchange Rate (FXR), Total Export (EXP). Trade Openness (TOR), Total Import (IMP), External Debt (EXTD), External Debt Service Charges, (EXDINT) and Foreign Direct Investment (FDIR), CBN is the source of the study data, spanning for a period of 1981 to 2020. The study applied Co-integration technique, Error Correction Model (ECM) and Granger Causality tests for the econometric analysis. Evidence from empirical results confirmed that, in the long run, only FDIR contributed positively to (RGDP), while the rest, had significant adverse effect on RGDP. The Granger Causality test established that only FDIR had bilateral relationship with RGDP while RGDP preceded EXP, TOR and FXR, implying that RGDP determines those variables without a feedback. EXTD, EXDINT and IMP maintained independent causal relationship. The ECM coeficient (-1.14), is significant and correctly signed (negative). It measures the speed of the adjustment, at which equilibrium is restored to RGDP, after the short-run disequilibrium in the selected indices. The implication is that RGDP growth process in Nigeria, in the long run, adjusts slowly to the changes in the selected indices, indicating a Policy lag effect. Consequently, Monetary authority should maintain efficient debt monitoring and management; effective and sustainable exchange rate management; infrastructural and technological development to beep up exportation. They should lay emphasis on stable political environment and sustainable economic policies to encourage more FDI. The Policy makers should make policies that would match the magnitude of the expected changes.

Pharmacological affinity fingerprints derived from bioactivity data for the identification of designer drugs

Facing the continuous emergence of new psychoactive substances (NPS) and their threat to public health, more effective methods for NPS prediction and identification are critical. In this study, the pharmacological affinity fingerprints (Ph-fp) of NPS compounds were predicted by Random Forest classification models using bioactivity data from the ChEMBL database. The binary Ph-fp is the vector consisting of a compound’s activity against a list of molecular targets reported to be responsible for the pharmacological effects of NPS. Their performance in similarity searching and unsupervised clustering was assessed and compared to 2D structure fingerprints Morgan and MACCS (1024-bits ECFP4 and 166-bits SMARTS-based MACCS implementation of RDKit). The performance in retrieving compounds according to their pharmacological categorizations is influenced by the predicted active assay counts in Ph-fp and the choice of similarity metric. Overall, the comparative unsupervised clustering analysis suggests the use of a classification model with Morgan fingerprints as input for the construction of Ph-fp. This combination gives satisfactory clustering performance based on external and internal clustering validation indices.

Assessment of radiological health risk and radiogenic heat production changeability of different sedimentary rocks at Gabal Um Hamd, Southwestern Sinai, Egypt

Soil is a source of natural radionuclides and a source of natural radiation risk to humans. This study aims to measure the radioactivity concentrations, contributions, radiological hazards and to quantify the radiogenic heat productions in thirty two rock samples having different lithology from the middle member of Um Bogma Formation in Gabal Um Hamd, southwestern Sinai, Egypt. The concentration of natural radionuclides was determined using a p-type Hyper Pure Germanium (HPGe) detector. The average activity concentrations of uranium thorium and potassium in the interested area were found to be 4909.58 ± 54.34 5003.12 ± 17.56 79.04 ± 8.82 and 137.35 ± 8.64 respectively. Other hazard indices average values were measured, such as: annual effective dose equivalent, radium equivalent activity, external and internal indices, annual gonad equivalent dose, and excess lifetime cancer risk. The radiologic hazards results, obtained in this study shows that the radiation levels are higher than the internationally approved values and the recommended safety limits. Furthermore, the results show that the radiogenic heat value ranged from 3.58 to 402.45 μW m −3 with an average value of 60.11 ± 0.79μW m −3 in the studied area which is higher than previously reported averages.

Measurement of activity concentrations of rock samples from rocks- surrounded town in Igbeti, Oyo State, Nigeria

Rocks are known to contain radionuclides that emit radiation continuously. The assessment of activity concentrations of rock samples from Igbeti, Oke-Ogun has been investigated. Twenty (20) rock samples were randomly collected from different rock sites. The rock samples were pulverized at the laboratory of the Department of Geology, University of Ibadan. 200g of each collected sample was allowed to attain secular equilibrium by enclosing it in a plastic container for twenty-eight (28) days. Radiometric analysis of the samples was carried out at the radiation laboratory of the Physics Department of the Federal University of Agriculture, Abeokuta using a thallium doped Sodium Iodide detector. Standard equations were used to estimate the radiological parameters associated with exposure to ionizing radiation from the natural radionuclides in the rock samples. The study revealed that the activity concentrations of 226Ra, 232Th, and 40K lie between 14 ̶ 487 (Bq/kg), 210 ̶ 3680 (Bq/kg), and 242 ̶ 1580 (Bq/kg) respectively. The absorbed dose rate (nGy/h), annual effective dose equivalent (μSv/y), (radium equivalent (Bq/kg), external and internal indices, activity utilization index and estimated excess lifetime cancer risks lie between from (180 ̶ 2700) nGy/h, (0.10 ̶ 14), 400 ̶ 6300 (Bq/kg), 1 ̶ 17, 1 ̶ 19, 2 ̶ 41, and 0.6 ̶ 9.5 × 10−6 respectively. The values of the absorbed dose rates value are greater than the world average of 60 nGy/h while annual effective dose equivalent values are less than the world’s average value of 1000 μSv/y respectively. The external and internal indices are greater than the permissible limit of (1) and likewise, the radium equivalent value is also greater than the acceptable limit of 370 Bq/kg. The estimated excess lifetime cancer risk for the study is below the permissible limit of 2.9 × 10−4 . Most of the estimated radiological parameters for the study are all greater than the permissible limit. This suggests that further exposure of dwellers to ionizing radiation may be possible and this calls for further investigation.

The differential impacts of coercive pressure from environmental law and proactive environmental strategy on corporate environmental performance: The case study of a pulp and paper company

AbstractPulp and paper companies are characterized by high‐energy consumption and high‐emission in production, placing a heavy burden on the environment. Exploring ways to improve their environmental performance is urgently needed. External coercive pressure from environmental law and internal proactive environmental strategy both enable companies to perform better, but little is known about the difference between them. To close this knowledge gap, our analysis is conducted on a case company in pulp and paper industry to compare the differential impacts of the New Environmental Protection Law of China and the proactive environmental strategy on its environmental performance. In addition, accurately evaluating the environmental performance of pulp and paper companies is essential while research on this topic is scant. Therefore, a novel environmental performance evaluation system for pulp and paper companies (EPESPP) is constructed, including not only internal but also external evaluation indexes based on news reports of various media measured by SNOWNLP sentiment analysis. According to the system, the environmental performance of the case company from 2010 to 2018 is evaluated by the entropy‐weight‐based catastrophe progression method (EWCPM). The results of our case study show that the implementation of a proactive environmental strategy is more conducive to comprehensively improving corporate environmental performance. In other words, the driving effect of the New Environmental Protection Law is not as strong as that of the proactive environmental strategy.

The effect of dietary coenzyme Q10 supplementation on egg quality and liver histopathology of layer quails under cadmium challenge.

The demand for quail eggs has been increased over the last decade due to its beneficial nutritional quality characteristics; however, different nutritional and environmental stressors adversely impact the quality of the produced eggs. This study was conducted to investigate whether dietary supplementation of coenzyme Q10 (CoQ10) could mitigate the negative impact of cadmium (Cd) administration on egg quality and liver histopathology. A total of 162 six-week-old laying Japanese quail (Coturnix japonica) were randomly allotted into three experimental groups. Treatments were as follows: (1) negative control (NC): feeding basal diet; (2) positive control (PC): feeding basal diet and Cdadministration; and (3) CdQ10: feeding basal diet supplemented with CoQ10 (900 mg/kg diet) and Cd administration. Cadmium (10 mg/kg BW) was subcutaneously administrated at 10 and 11 weeks of age (woa). Feed conversion ratio (FCR), egg production, egg mass, mortality rate, Cd residue in egg, liver histopathology, and some internal and external egg quality indices were evaluated. Administration of Cd increased FCR in the PC group, but supplementation of CoQ10 partially ameliorated the impact of Cd on FCR (p < 0.05). Cadmium administration decreased both egg production and egg mass; however, CoQ10 supplementation partially mitigated these adverse effects of Cd injection in the CdQ10 compared to the PC group (p < 0.05). Cadmium decreased eggshell thickness and Haugh unit in PC quail compared to both NC and CdQ10 quail (p < 0.05). Moreover, egg yolk colour intensity was enhanced by CoQ10, where a* and b* indices were higher in CdQ10 compared to PC (p < 0.05). In conclusion, the current results demonstrate the beneficial effects of dietary CoQ10 supplementation on liver histopathology and some egg quality indices of Cd-challenged quail.

Multimodal Web Page Segmentation Using Self-organized Multi-objective Clustering

Web page segmentation (WPS) aims to break a web page into different segments with coherent intra- and inter-semantics. By evidencing the morpho-dispositional semantics of a web page, WPS has traditionally been used to demarcate informative from non-informative content, but it has also evidenced its key role within the context of non-linear access to web information for visually impaired people. For that purpose, a great deal of ad hoc solutions have been proposed that rely on visual, logical, and/or text cues. However, such methodologies highly depend on manually tuned heuristics and are parameter-dependent. To overcome these drawbacks, principled frameworks have been proposed that provide the theoretical bases to achieve optimal solutions. However, existing methodologies only combine few discriminant features and do not define strategies to automatically select the optimal number of segments. In this article, we present a multi-objective clustering technique called MCS that relies on \( K \) -means, in which (1) visual, logical, and text cues are all combined in a early fusion manner and (2) an evolutionary process automatically discovers the optimal number of clusters (segments) as well as the correct positioning of seeds. As such, our proposal is parameter-free, combines many different modalities, does not depend on manually tuned heuristics, and can be run on any web page without any constraint. An exhaustive evaluation over two different tasks, where (1) the number of segments must be discovered or (2) the number of clusters is fixed with respect to the task at hand, shows that MCS drastically improves over most competitive and up-to-date algorithms for a wide variety of external and internal validation indices. In particular, results clearly evidence the impact of the visual and logical modalities towards segmentation performance.